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PhD Dissertation Defense Slides Design: Start

  • Tips for designing the slides
  • Presentation checklist
  • Example slides
  • Additional Resources

Purpose of the Guide

This guide was created to help ph.d. students in engineering fields to design dissertation defense presentations. the guide provides 1) tips on how to effectively communicate research, and 2) full presentation examples from ph.d. graduates. the tips on designing effective slides are not restricted to dissertation defense presentations; they can be used in designing other types of presentations such as conference talks, qualification and proposal exams, and technical seminars., the tips and examples are used to help students to design effective presentation. the technical contents in all examples are subject to copyright, please do not replicate. , if you need help in designing your presentation, please contact julie chen ([email protected]) for individual consultation. .

  • Example Slides Repository
  • Defense slides examples Link to examples dissertation defense slides.

Useful Links

  • CIT Thesis and dissertation standards
  • Dissertations and Theses @ Carnegie Mellon This link opens in a new window Covers 1920-present. Full text of some dissertations may be available 1997-present. Citations and abstracts of dissertations and theses CMU graduate students have published through UMI Dissertation Publishing. In addition to citations and abstracts, the service provides free access to 24 page previews and the full text in PDF format, when available. In most cases, this will be works published in 1997 forward.
  • Communicate your research data Data visualization is very important in communicating your data effectively. Check out these do's and don'ts for designing figures.

Power Point Template and other Resources

  • CEE Powerpoint Slide Presentation Template 1
  • CEE Powerpoint Slide Presentation Template 2

Source: CEE Department Resources https://www.cmu.edu/cee/resources/index.html

  • CMU Powerpoint Slide Template

Source: CMU Marketing and Communications

https://www.cmu.edu/marcom/brand-standards/downloads/index.html

  • Use of CMU logos, marks, and Unitmarks

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Top 7 tips for your defense presentation

1. show why your study is important, remember, your audience is your committee members, researchers in other fields, and even the general public. you want to convince all of them why you deserve a ph.d. degree. you need to talk about why your study is important to the world. in the engineering field, you also need to talk about how your study is useful. try to discuss why current practice is problematic or not good enough, what needs to be solved, and what the potential benefits will be. , see how dr. posen and dr. malings explained the importance of their studies..

  • Carl Malings Defense Slides with Notes
  • I. Daniel Posen Defense Slides with Notes

2. Emphasize YOUR contribution 

Having a ph.d. means that you have made some novel contributions to the grand field. this is about you and your research. you need to keep emphasizing your contributions throughout your presentation. after talking about what needs to be solved, try to focus on emphasizing the novelty of your work. what problems can be solved using your research outcomes what breakthroughs have you made to the field why are your methods and outcomes outstanding you need to incorporate answers to these questions in your presentation. , be clear what your contributions are in the introduction section; separate what was done by others and what was done by you. , 3. connect your projects into a whole piece of work, you might have been doing multiple projects that are not strongly connected. to figure out how to connect them into a whole piece, use visualizations such as flow charts to convince your audience. the two slides below are two examples. in the first slide, which was presented in the introduction section, the presenter used a flow diagram to show the connection between the three projects. in the second slide, the presenter used key figures and a unique color for each project to show the connection..

phd proposal presentation outline

  • Xiaoju Chen Defense Slides with Notes

4. Tell a good story 

The committee members do not necessarily have the same background knowledge as you. plus, there could be researchers from other fields and even the general public in the room. you want to make sure all of your audience can understand as much as possible. focus on the big picture rather than technical details; make sure you use simple language to explain your methods and results. your committee has read your dissertation before your defense, but others have not. , dr. cook and dr. velibeyoglu did a good job explaining their research to everyone. the introduction sessions in their presentations are well designed for this purpose. .

  • Laren M. Cook Defense Slides with Notes
  • Irem Velibeyoglu Defense with Notes

5. Transition, transition, transition

Use transition slides to connect projects , it's a long presentation with different research projects. you want to use some sort of transition to remind your audience what you have been talking about and what is next. you may use a slide that is designed for this purpose throughout your presentation. , below are two examples. these slides were presented after the introduction section. the presenters used the same slides and highlighted the items for project one to indicate that they were moving on to the first project. throughout the presentation, they used these slides and highlighted different sections to indicate how these projects fit into the whole dissertation. .

phd proposal presentation outline

You can also use some other indications on your slides, but remember not to make your slides too busy.  Below are two examples. In the first example, the presenter used chapter numbers to indicate what he was talking about. In the second example, the presenter used a progress bar with keywords for each chapter as the indicator. 

phd proposal presentation outline

Use transition sentences to connect slides 

Remember transition sentences are also important; use them to summarize what you have said and tell your audience what they will expect next. if you keep forgetting the transition sentence, write a note on your presentation. you can either write down a full sentence of what you want to say or some keywords., 6. be brief, put details in backup slides , you won't have time to explain all of the details. if your defense presentation is scheduled for 45 minutes, you can only spend around 10 minutes for each project - that's shorter than a normal research conference presentation focus on the big picture and leave details behind. you can put the details in your backup slides, so you might find them useful when your committee (and other members of the audience) ask questions regarding these details., 7. show your presentation to your advisor and colleagues, make sure to ask your advisor(s) for their comments. they might have a different view on what should be emphasized and what should be elaborated. , you also want to practice at least once in front of your colleagues. they can be your lab mates, people who work in your research group, and/or your friends. they do not have to be experts in your field. ask them to give you some feedback - their comments can be extremely helpful to improve your presentation. , below are some other tips and resources to design your defense presentation. .

  • Tips for designing your defense presentation

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phd proposal presentation outline

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phd proposal presentation outline

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Research Tips and Infromation

Ph.D. Proposal Presentation Template

A Ph.D. proposal presentation template is a pre-designed set of slides that can be used as a starting point for creating a presentation for your Ph.D. proposal Registration. It includes a series of suggested slides, which you can customize to your specific needs. This template can be used by Ph.D. candidates from various fields who are preparing for their Ph.D. registration.

Slide 1: Title Slide

  • Title of the work
  • Candidate’s name and affiliation
  • Supervisor’s name and affiliation

Slide 2: Introduction

  • Briefly introduce the topic
  • Explain why the topic is important and relevant
  • Provide a brief overview of what the presentation will cover

Slide 3: Literature Review

  • Summarize the key findings of relevant literature
  • Identify gaps and limitations in the existing research
  • Explain how your work will contribute to filling these gaps

Slide 4: Motivation and Research Problem

  • Explain the motivation behind your work
  • Clearly state the research problem you are addressing

Slide 5: Research Question and Objectives

  • State your research question
  • Clearly articulate your research objectives

Slide 6: Study Design and Methods

  • Explain your study design and why you chose it
  • Describe your data collection methods and measures

Slide 7: Predicted Outcomes

  • Present your predicted outcomes if everything goes according to plan
  • Explain how these outcomes will contribute to the field

Slide 8: Resources

  • Identify the resources you will need to complete your work
  • Explain how you will obtain these resources

Slide 9: Societal Impact

  • Describe the potential societal impact of your work
  • Explain how your work will benefit society

Slide 10: Gantt Chart

  • Present a Gantt chart representing the timetable of the activities planned
  • Explain how you will manage your time to complete your work on schedule

Slide 11: Potential Challenges

  • Identify potential challenges you may encounter during your research
  • Explain how you plan to address these challenges

Slide 12: Conclusion

  • Summarize the key points of your presentation
  • Conclude by emphasizing the significance of your work and its potential impact

Slide 13: Questions

  • Encourage the audience to ask questions
  • Thank the audience for their attention

Remember to keep your presentation simple, well-structured, and effective. Use clear and concise language, and make sure your presentation is visually engaging. Good luck with your PhD proposal presentation!

  • Title of the work: “A Comparative Study of Deep Learning Techniques for Image Recognition in Medical Imaging”
  • Candidate’s name and affiliation: Sarah Johnson, Department of Computer Science, University of ABC
  • Supervisor’s name and affiliation: Dr. Robert Lee, Department of Computer Science, University of ABC

In this slide, you have to include the title of your work, your name and affiliation as the PhD candidate, and your supervisor’s name and affiliation. The title should be concise and descriptive, conveying the essence of your research.

  • Briefly introduce the topic: Deep Learning Techniques for Image Recognition in Medical Imaging
  • Explain why the topic is important and relevant: Accurate and efficient image recognition in medical imaging is crucial for diagnosis, treatment planning, and monitoring of patient progress. However, the current state-of-the-art algorithms still have limitations in handling the complexities of medical images, such as noise, variation in size and shape, and variation in imaging protocols.
  • Provide a brief overview of what the presentation will cover: In this presentation, I will introduce my proposed research on a comparative study of deep learning techniques for image recognition in medical imaging. I will briefly cover the literature review, the research problem and goals, the study design, and the expected outcomes of the research.

In this slide, you have to provide an introduction to your research topic, explaining its importance and relevance in the field. The introduction should set the context for your research and explain why it matters.

  • Summarize the key findings of relevant literature: Previous research has shown that deep learning techniques, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs), have achieved state-of-the-art results in various image recognition tasks, including medical image recognition. However, the performance of these techniques can be affected by factors such as the size and complexity of the dataset, the selection of hyperparameters, and the choice of architecture.
  • Identify gaps and limitations in the existing research: While previous studies have compared the performance of different deep learning techniques for image recognition in general, there is a lack of research that compares and evaluates the performance of these techniques specifically in medical imaging. Additionally, there is a need for research that investigates the effectiveness of transfer learning, data augmentation, and other techniques for improving the performance of deep learning models in medical image recognition tasks.
  • Explain how your work will contribute to filling these gaps: The proposed research aims to contribute to filling these gaps by conducting a comparative study of various deep learning techniques for image recognition in medical imaging. The study will also investigate the effectiveness of transfer learning, data augmentation, and other techniques for improving the performance of these techniques in medical image recognition tasks. The results of this study will provide valuable insights into the strengths and limitations of different deep-learning techniques in medical imaging, and help inform the development of more accurate and efficient algorithms in the future.

In this slide, you have to summarize the key findings of relevant literature in your research area, identify gaps and limitations in the existing research, and explain how your work will contribute to filling these gaps.

Slide 3: Literature Review
– Deep learning techniques (e.g. CNNs, RNNs) have achieved state-of-the-art results in various image recognition tasks, including medical image recognition.
– Performance can be affected by factors such as dataset size and complexity, hyperparameter selection, and architecture choice.
– Lack of research comparing and evaluating deep learning techniques specifically in medical imaging.
– Need for investigation of transfer learning, data augmentation, and other techniques for improving deep learning model performance in medical image recognition tasks.
– Conduct a comparative study of various deep learning techniques for image recognition in medical imaging.
– Investigate the effectiveness of transfer learning, data augmentation, and other techniques for improving deep learning model performance in medical image recognition tasks.
– Provide valuable insights into the strengths and limitations of different deep learning techniques in medical imaging, and help inform the development of more accurate and efficient algorithms in the future.

In this format, the information is organized into three sections: key findings, gaps and limitations, and contribution of proposed work. Each section is presented as a bullet point, with the main idea in bold, followed by a brief explanation. This format can be useful for presenting information in a clear and concise manner, while still providing enough detail to convey the main points.

Slide 4: Motivation and Research Problem
– Medical image recognition is an important application with significant potential for improving patient outcomes.
– Deep learning techniques have shown promise in this area, but their effectiveness depends on various factors, and there is still room for improvement.
– A comprehensive study of deep learning techniques for medical image recognition could help identify the most effective approaches and guide future research.
– The goal of this research is to conduct a comparative study of deep learning techniques for image recognition in medical imaging and investigate the effectiveness of transfer learning, data augmentation, and other techniques for improving model performance.
– Specifically, we aim to address the following research questions:
– What are the relative strengths and weaknesses of different deep-learning techniques for medical image recognition?
– How can transfer learning and data augmentation be used to improve model performance?
– What are the key factors affecting model performance, and how can they be optimized?

In this format, the motivation and research problem are presented as two separate sections, with each section consisting of bullet points. The motivation section explains why the topic is important and why the proposed research is needed, while the research problem section clearly states the specific questions that the research will address. This format can help ensure that the motivation and research problem are clearly articulated and easy to understand.

Slide 5: Research Question and Objectives
– What are the most effective deep-learning techniques for medical image recognition, and how can they be optimized for improved performance?
– To conduct a comparative study of deep learning techniques for image recognition in medical imaging, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and hybrid models.
– To investigate the effectiveness of transfer learning, data augmentation, and other techniques for improving model performance.
– To identify the key factors affecting model performance, including dataset size, complexity, and quality, and optimize these factors for improved accuracy and efficiency.
– To develop a comprehensive set of guidelines for using deep learning techniques in medical image recognition, based on the results of the study.

In this format, the research question and research objectives are presented as two separate sections, with each section consisting of bullet points. The research question clearly states the specific problem that the research will address, while the research objectives explain the specific goals that the research aims to achieve in order to answer the research question. This format can help ensure that the research question and objectives are clearly articulated and easy to understand.

Slide 6: Study Design and Methods
– Comparative study of deep learning techniques for medical image recognition.
– Experimental design with three groups: one using convolutional neural networks (CNNs), one using recurrent neural networks (RNNs), and one using hybrid models.
– Randomized assignment of datasets to groups to control for confounding factors.
– Datasets: Publicly available medical image datasets, including the MURA, ChestX-ray8, and DeepLesion datasets.
– Measures: Accuracy, sensitivity, specificity, and AUC for image recognition.
– Methods: Each group will train and test their models on the same datasets, with performance measures recorded for each model.

In this format, the study design and data collection methods are presented as two separate sections, with each section consisting of bullet points. The study design section provides an overview of the design of the study, including the specific groups being compared and the methods used to control for confounding factors. The data collection methods section describes the datasets and measures being used, as well as the specific methods being employed to train and test the deep learning models. This format can help ensure that the study design and methods are clearly explained and easy to understand.

Slide 7: Predicted Outcomes
– The CNN group is predicted to achieve the highest accuracy and AUC scores for medical image recognition.
– The hybrid model group is predicted to achieve high sensitivity and specificity scores, making it well-suited for certain medical applications.
– The RNN group is predicted to perform well on image sequences, such as those in medical videos or time-lapse images.
– This study will provide a comparative analysis of deep learning techniques for medical image recognition, helping to identify which techniques are most effective for different applications.
– The study will contribute to the development of improved medical image recognition models, which can have a significant impact on patient care and treatment outcomes.

In this format, the predicted outcomes are presented as bullet points, along with an explanation of how they will contribute to the field. The predicted outcomes are based on the study design and methods described in previous slides and can help to demonstrate the potential impact of the proposed research.

Slide 8: Resources
– Access to medical image databases with labeled images for model training and testing.
– Powerful computing resources, such as GPUs, for running deep learning algorithms.
– Software tools for image pre-processing, deep learning model training, and model evaluation.
– Technical support for troubleshooting and optimizing software and hardware issues.
– Medical image databases will be obtained through collaborations with healthcare institutions and research organizations.
– Computing resources will be obtained through the university’s high-performance computing center.
– Software tools will be obtained through open-source repositories and commercial licenses as needed.
– Technical support will be provided by the university’s IT department and by contacting software vendors and community forums as needed.

This slide presents the resources needed to complete the work, along with an explanation of how these resources will be obtained. This can help to demonstrate that the necessary resources have been identified and that a plan is in place to obtain them.

Slide 9: Societal Impact
– Improving the accuracy and efficiency of medical image analysis can lead to more accurate and timely diagnoses, which can improve patient outcomes and reduce healthcare costs.
– Developing robust and interpretable deep learning models can help to build trust in these technologies and enable their widespread adoption in clinical practice.
– Generating new insights into brain tumor growth and progression can help to guide treatment decisions and lead to more personalized and effective therapies.
– By improving medical image analysis, our work can help to reduce the time and cost of diagnosis, increase the accuracy of treatment planning, and ultimately improve patient outcomes.
– By developing more interpretable and trustworthy deep learning models, our work can help to facilitate their integration into clinical practice and improve patient care.
– By providing new insights into brain tumor growth and progression, our work can help to guide the development of more targeted and effective treatments.

This slide presents the potential societal impact of the work and how it will benefit society. This can help to demonstrate the broader implications and significance of the research.

Work breakdown  of PhD work

Gnatt chart representing the timetable of the activities planned

You have to create a Gantt chart to represent the activities that are planned for completing this research work within the given time frame. The time frame can change depending on the Univesity’s stipulated guidelines for full-time and part-time Ph.D. programs.

The chart is divided into five different stages, which are:

  • Completion of the Course Work: You need to complete the coursework papers as per University Guidelines. This stage is expected to take 12 months.
  • Literature review: In this stage, we will review and analyze the existing literature to identify gaps and limitations in the research. This stage is expected to take 06 months.
  • Data collection: In this stage, we will collect the required data by conducting experiments and surveys. This stage is expected to take 06 months.
  • Data analysis: In this stage, we will analyze the collected data to draw meaningful insights and conclusions. This stage is expected to take 3 months.
  • Model development: In this stage, we will develop the proposed model and implement it. This stage is expected to take 12 months.
  • Results and Analysis: In this stage, we will gather the results from various dimensions of the proposed model and analyze them. This stage is expected to take 03 months.
  • Writing and submission: In this stage, we will write and submit the final research report and the thesis. This stage is expected to take 06 months.

You have to allocate appropriate time for each stage to complete the work on schedule. You have to keep track of the progress regularly and make necessary adjustments to the plan to ensure the timely completion of the research work.

In this section, you have to discuss some potential challenges which you may encounter during your research and how you plan to address them.

Potential Challenges:

  • Access to data: Since we are planning to collect data from several sources, it may be challenging to obtain access to all the necessary data.
  • Time constraints: We have a strict timeline to follow, and any delays could affect the overall success of the project.
  • Technical difficulties: There is always a risk of encountering technical difficulties during data collection or analysis.

Addressing the Challenges:

  • Data access: We will communicate with the relevant authorities and request access to the data needed for our research. We will also explore alternative sources of data if necessary.
  • Time constraints: We will break down our research into smaller, more manageable tasks and allocate sufficient time for each. We will also build in extra time in case of unexpected delays.
  • Technical difficulties: We will test our data collection and analysis tools thoroughly beforehand to minimize the risk of technical difficulties. We will also have contingency plans in place in case of any issues that may arise.

By identifying potential challenges and having a plan in place to address them, you can ensure that your research progresses smoothly and efficiently.

In conclusion, this presentation has outlined a research proposal for a comparative study of deep learning techniques for image recognition in medical imaging. The key points covered in this presentation are:

  • The importance of developing accurate and efficient image recognition techniques for medical imaging, which can assist in the diagnosis and treatment of various medical conditions
  • A review of the relevant literature in this field has identified the need for further research to compare the performance of different deep-learning techniques for image recognition in medical imaging
  • The research problem, objectives, and research question, aim to address this need by comparing the performance of different deep-learning techniques for image recognition in medical imaging
  • The study design and methods, which will involve collecting and analyzing medical imaging data using various deep-learning techniques
  • The predicted outcomes of the study, which could contribute to improving the accuracy and efficiency of image recognition in medical imaging
  • The resources required to complete the study, including access to medical imaging data and computational resources
  • The potential societal impact of the study, which could benefit patients and healthcare providers by improving the accuracy and efficiency of medical imaging
  • The timetable of activities, which has been represented in a Gantt chart to ensure that the study is completed on schedule
  • The potential challenges that may be encountered during the research, and the strategies that will be used to address these challenges.

Overall, this research proposal has the potential to contribute to the field of medical imaging by providing valuable insights into the performance of different deep-learning techniques for image recognition. By improving the accuracy and efficiency of image recognition in medical imaging, this research could ultimately benefit patients and healthcare providers.

Download the PhD Proposal Presentation Template here:

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How to nail your PhD proposal and get accepted

Bethany Fagan

Bethany Fagan Head of Content Marketing at PandaDoc

Reviewed by:

Olga Asheychik

Olga Asheychik Senior Web Analytics Manager at PandaDoc

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A good PhD research proposal may be the deciding factor between acceptance and approval into your desired program or finding yourself back at the drawing board. Being accepted for a PhD placement is no easy task, and this is why your PhD proposal needs to truly stand out among a sea of submissions.

That’s why a PhD research proposal is important: It formally outlines the intended research, including methodology, timeline, feasibility, and many other factors that need to be taken into consideration.

Here is a closer look at the PhD proposal process and what it should look like.

→DOWNLOAD NOW: FREE PHD PROPOSAL TEMPLATE

Key takeaways

  • A PhD proposal summarizes the research project you intend to conduct as part of your PhD program.
  • These proposals are relatively short (1000-2000 words), and should include all basic information and project goals, including the methodologies/strategies you intend to use in order to accomplish them.
  • Formats are varied. You may be able to create your own formats, but your college or university may have a required document structure that you should follow.

What is a PhD proposal?

In short, a PhD research proposal is a summary of the project you intend to undertake as part of your PhD program.

It should pose a specific question or idea, make a case for the research, and explain the predicted outcomes of that research.

However, while your PhD proposal may predict expected outcomes, it won’t fully answer your questions for the reader.

Your research into the topic will provide that answer.

Usually, a PhD proposal contains the following elements:

  • A clear question that you intend to answer through copious amounts of study and research.
  • Your plan to answer that question, including any methodologies, frameworks, and resources required to adequately find the answer.
  • Why your question or project is significant to your specific field of study.
  • How your proposal impacts, challenges, or improves the existing body of knowledge around a given topic.
  • Why your work is important and why you should be the one to receive this opportunity.

In terms of length when writing a PhD proposal, there isn’t a universal answer.

Some institutions will require a short, concise proposal (1000 words), while others allow for a greater amount of flexibility in the length and format of the proposal.

Fortunately, most institutions will provide some guidelines regarding the format and length of your research proposal, so you should have a strong idea of your requirements before you begin.

Benefits of a strong PhD application

While the most obvious benefit of having a strong PhD application is being accepted to the PhD program , there are other reasons to build the strongest PhD application you can:

Better funding opportunities

Many PhD programs offer funding to students , which can be used to cover tuition fees and may provide a stipend for living expenses.

The stronger your PhD application, the better your chances of being offered funding opportunities that can alleviate financial burdens and allow you to focus on your research.

Enhanced academic credentials

A strong PhD application, particularly in hot-button areas of study, can lead to better career opportunities in academics or across a variety of industries.

Opportunities for networking and research

Research proposals that are very well grounded can provide footholds to networking opportunities and mentorships that would not be otherwise available.

However, creating an incredible proposal isn’t always easy.

In fact, it’s easy to get confused by the process since it requires a lot of procedural information.

Many institutions also place a heavy emphasis on using the correct proposal structure.

That doesn’t have to be the issue, though.

Often, pre-designed templates, like the PandaDoc research proposal templates or PhD proposal templates provided by the institution of your choice, can do most of the heavy lifting for you.

phd proposal presentation outline

Research Proposal Template

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How to write a Phd proposal with a clear structure

We know that the prospect of writing a research proposal for PhD admission may appear the stuff of nightmares. Even more so if you are new to producing a piece such as this.

But, when you get down to the nitty gritty of what it is, it really isn’t so intimidating. When writing your PhD proposal you need to show that your PhD is worth it, achievable, and that you have the ability to do it at your chosen university.

With all of that in mind, let’s take a closer look at each section of a standard PhD research proposal and the overall structure.

1. Front matter

The first pages of your PhD proposal should outline the basic information about the project. That will include each of the following:

Project title

Typically placed on the first page, your title should be engaging enough to attract attention and clear enough that readers will understand what you’re trying to achieve.

Many proposals also include a secondary headline to further (concisely) clarify the main concept.

Contact information

Depending on the instructions provided by your institution, you may need to include your basic contact information with your proposal.

Some institutions may ask for blind submissions and ask that you omit identifying information, so check the program guidelines to be sure.

Research supervisor

If you already have a supervisor for the project, you’ll typically want to list that information.

Someone who is established in the field can add credibility to your proposal, particularly if your project requires extensive funding or has special considerations.

The guidelines from your PhD program should provide some guidance regarding any other auxiliary information that you should add to the front of your proposal.

Be sure to check all documentation to ensure that everything fits into the designated format.

2. Goals, summaries, and objectives

Once you’ve added the basic information to your document, you’ll need to get into the meat of your PhD proposal.

Depending on your institution, your research proposal may need to follow a rigid format or you may have the flexibility to add various sections and fully explain your concepts.

These sections will primarily be focused on providing high-level overviews surrounding your PhD proposal, including most of the following:

Overall aims, objectives, and goals

In these sections, you’ll need to state plainly what you aim to accomplish with your PhD research.

If awarded funding, what questions will your PHd proposal seek to answer? What theories will you test? What concepts will you explore in your research?

Briefly, how would you summarize your approach to this project?

Provide high-level summaries detailing how you mean to achieve your answers, what the predicted outcomes of your PhD research might be, and precisely what you intend to test or discover.

Significance

Why does your research matter? Unlike with many other forms of academic study (such as a master’s thesis ), doctorate-level research often pushes the bounds of specific fields or contributes to a given body of work in some unique way.

How will your proposed PhD research do those things?

Background details

Because PhD research is about pushing boundaries, adding background context regarding the current state of affairs in your given field can help readers better understand why you want to pursue this research and how you arrived at this specific point of interest.

While the information here may (or may not) be broken into multiple sections, the content here is largely designed to provide a high-level overview of your PhD proposal and entice readers to dig deeper into the methodologies and angles of approach in future sections.

Because so much of this section relies on the remainder of your document, it’s sometimes better to skip this portion of the PhD proposal until the later sections are complete and then circle back to it.

That way, you can provide concise summaries that refer to fully defined research methods that you’ve already explained in subsequent areas.

3. Methodologies and plans

Unlike a master’s thesis or a similar academic document, PhD research is designed to push the boundaries of its subject matter in some way.

The idea behind doctoral research is to expand the field with new insights and viewpoints that are the culmination of years of research and study, combined with a deep familiarity of the topic at hand.

The methodologies and work plans you provide will give advisors some insights into how you plan to conduct your research.

While there is no one right way to develop this section, you’ll need to include a few key details:

Research methods

Are there specific research methods you plan to use to conduct your PhD research?

Are you conducting experiments? Conducting qualitative research? Surveying specific individuals in a given environment?

Benefits and drawbacks of your approach

Regardless of your approach to your topic, there will be upsides and downsides to that methodology.

Explain what you feel are the primary benefits to your research method, where there are potential flaws, and how you plan to account for those shortfalls.

Choice of methodology

Why did you choose a given methodology?

What makes it the best method (or collection of methods) for your research and/or specific use case?

Outline of proposed work

What work is required for PhD research to be complete?

What steps will you need to take in order to capture the appropriate information? How will you complete those steps?

Schedule of work (including timelines/deadlines)

How long will it take you to complete each stage or step of your project?

If your PhDproject will take several years, you may need to provide specifics for more immediate timelines up front while future deadlines may be flexible or estimated.

There is some flexibility here.

It’s unlikely that your advisors will expect you to have the answer for every question regarding how you plan to approach your body of research.

When trying to push the boundaries of any given topic, it’s expected that some things may not go to plan.

However, you should do your best to make timelines and schedules of work that are consistent with your listed goals.

Remember : At the end of your work, you are expected to have a body of original research that is complete within the scope and limitations of the PhD proposal you set forth.

If your advisors feel that your subject matter is too broad, they may encourage you to narrow the scope to better fit into more standardized expectations.

4. Resources and citations

No PhD research proposal is complete without a full list of the resources required to carry out the project and references to help prove and validate the research.

Here’s a closer look at what you’ll need to submit in order to explain costs and prove the validity of your proposal:

Estimated costs and resources

Most doctoral programs offer some level of funding for these projects.

To take advantage of those funds, you’ll need to submit a budget of estimated costs so that assessors can better understand the financial requirements.

This might include equipment, expenses for fieldwork or travel, and more.

Citations and bibliographies

No matter your field of study, doctoral research is built on the data and observations provided by past contributors.

Because of this, you’ll need to provide citations and sources referenced in your PhD proposal documentation.

Particularly when it comes to finances and funding, it might be tempting to downplay the cost of the project.

However, it’s best to provide a realistic estimate in terms of costs so that you have enough of a budget to cover the PhD research.

Adjustments can be made at a later date, particularly as you conduct more research and dive further into the project.

Resources are often presented in the form of a table to make things easier to track and identify.

Item Qty. Cost Subtotal Total
Project Allowance
Translator 3 months $500 $1,500
Transportation within state 3 months $400 $1,200
Interview software 1 month $30 $30
Recording equipment 1 $2,400 $2,400
Rent (Nigeria) 3 months $400 $1,200
Groceries (Nigeria) 3 months $500 $1,500
$8,100
Jet Travel
San Diego – Nigeria (roundtrip) 6 $600 $3,600 $3,600
Total Project Allowance $11,700
Administrative fees $240
Total Resources $11,940

Using PhD proposal templates

Aside from any guidelines set forth by your institution, there are no particularly strict rules when it comes to the format of PhD proposals.

Your supervisor will be more than capable of guiding you through the process.

However, since everything is so structured and formal, you might want to use a PhD proposal template to help you get started.

Templates can help you stay on track and make sure your research proposal follows a certain logic.

A lot of proposal software solutions offer templates for different types of proposals, including PhD proposals.

But, should you use Phd proposal templates? Here are some pros and cons to help you make a decision.

  • Expedites the proposal process.
  • Helps you jumpstart the process with a flexible document structure.
  • Often provides sections with pre-filled examples.
  • Looks better than your average Word document.
  • May be limiting if you adhere to it too much.
  • Might not be perfectly suited to your specific field of research, requiring some customization.

In our PhD research proposal template , we give you just enough direction to help you follow through but we don’t limit your creativity to a point that you can’t express yourself and all the nuances of your research.

For almost all sections, you get a few useful PhD research proposal examples to point you in the right direction.

The template provides you with a typical PhD proposal structure that’s perfect for almost all disciplines.

It can come in quite handy when you have everything planned out in your head but you’re just having trouble putting it onto the page!

Writing a PhD proposal that convinces

Writing and completing a PhD proposal might be confusing at first.

You need to follow a certain logic and share all the required information without going too long or sharing too much about the project.

And, while your supervisor will certainly be there to guide you, the brunt of the work will still fall on your shoulders.

That’s why you need to stay informed, do your research, and don’t give up until you feel comfortable with what you’ve created.

If you want to get a head start, you might want to consider our research proposal template .

It will offer you a structure to follow when writing a PhD proposal and give you an idea on what to write in each section.

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Research proposals for PhD admission: tips and advice

One of the most important tips for any piece of writing is to know your audience. The staff reviewing your PhD proposal are going through a pile of them, so you need to make sure yours stands within a few seconds of opening it.

The way to do this is by demonstrating value and impact. Academic work is often written for a niche community of researchers in one field, so you need to demonstrate why your work would be valuable to people in that area.

The people reviewing your proposal will likely be in that field. So your proposal should be a little like a sales pitch: you need to write something engaging that identifies with the “customer”, speaks to a problem they’re having, and shows them a solution.

Taking some inspiration from the former University of Chicago professor Larry McEnerney , here are some ideas to keep in mind…

  • It’s common for undergraduates and even seasoned academics to write in a specific format or style to demonstrate their understanding and signal that they’re part of the academic community. Instead, you want to write in such a way that actually engages the reader.
  • Identify an uncharted or underexplored knowledge gap in your field, and show the reader you have what it takes to fill in that gap.
  • Challenge the status quo. Set up an idea that people in your field take for granted — maybe a famous study you think is flawed — and outline how your project could knock it down.
  • This is why it’s important to understand who your audience is. You have to write your proposal in such a way that it’s valuable for reviewers. But within your proposal, you should also clearly define which community of researchers your project is for, what problems they have, and how your project is going to solve those problems.
  • Every community of researchers has their own implicit “codes” and “keywords” that signal understanding. These will be very different in each field and could be very subtle. But just by reading successful PhD research proposal examples in your field, you can get a sense of what those are and decide how you want to employ them in your own work.
  • In this model authors start “at the bottom of the glass” with a very narrow introduction to the idea of the paper, then “fill the glass” with a broader and broader version of the same idea.
  • Instead, follow a “problem-solution” framework. Introduce a problem that’s relevant to your intended reader, then offer a solution. Since “solutions” often raise their own new problems or questions, you can rinse and repeat this framework all the way through any section of your proposal.

But how can you apply that advice? If you’re following something like our research proposal template , here are some actionable ways to get started.

  • Your title should be eye-catching , and signal value by speaking to either a gap in the field or challenging the status quo.
  • Your abstract should speak to a problem in the field, one the reviewers will care about, and clearly outline how you’d like to solve it.
  • When you list the objectives of your proposal , each one should repeat this problem-solution framework. You should concretely state what you want to achieve, and what you’re going to do to achieve it.
  • While you survey your chosen field in the literature review, you should refer back to the knowledge gap or status quo that you intend to work on. This reinforces how important your proposed project is, and how valuable it would be to the community if your project was successful.
  • While listing your research limitations , try to hint at new territory researchers might be able to explore off the back of your work. This illustrates that you’re proposing boundary-pushing work that will really advance knowledge of the field.
  • While you’re outlining your funding requirements , be clear about why each line item is necessary and bring it back to the value of your proposed research. Every cent counts!

Frequently asked questions

How long should a phd proposal be.

There really isn’t a specific rule when it comes to the length of a PhD proposal. However, it’s generally accepted that it should be between 1,000 and 2,000 words.

It’s difficult to elaborate on such a serious project in less than 1,000 words but going over 2,000 is often overkill. You’ll lose people’s attention and water down your points.

What’s the difference between a dissertation proposal and a PhD proposal?

There seems to be some confusion over the terms “dissertation” and “PhD” and how you write proposals for each one. However, “dissertation” is just another name for your PhD research so the proposal for a dissertation would be the same since it’s quite literally the same thing.

Does a PhD proposal include budgeting?

Yes, as mentioned, you need to demonstrate the feasibility of your project within the given time frame and with the resources you need, including budgets. You don’t need to be exact, but you need to have accurate estimates for everything.

How is a PhD proposal evaluated?

This will change from one institution to another but these things will generally have a big impact on the reviewers:

  • The contribution of the project to the field.
  • Design and feasibility of the project.
  • The validity of the methodology and objectives.
  • The supervisor and their role in the field.

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Originally published June 9, 2023, updated February 6, 2024

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