Doctor of Philosophy in Natural, Mathematical, and Computational Sciences

To successfully translate research into new products and services that are beneficial for human and planetary health - you need to develop clear insights into the rigorous and fulfilling journey of today’s deep tech founders. Key to this journey is being able to skilfully navigate the landscape of dilutive and non-dilutive deep tech funding opportunities.

By analysing investment opportunities using the same lenses of deep tech funders, you will be able to evaluate key investment criteria funders use to perform their investment decision-making and develop strong negotiation skills.

Course Goal

By the end of this course, you will be able to evaluate varying perspectives and approaches across deep tech funders of what it means to be an investable company and founder. You will be able to build qualitative and quantitative assessments on many of the key dimensions deep tech funders use in their due diligence. And you will become fluent in the key terms and concepts funders use throughout their due diligence and investment proposal processes.

Course Project

In your final project, you will experience making and accepting an investment offer to a deep tech company of your choice. You will draft the key terms of an investment proposal, and critically analyze its impact on a company’s value and governance.

Stochastic processes have driven and enhanced human creativity and learning throughout the history of science and entrepreneurship. This somewhat unpredictable exploration of the unknown in the pursuit of new knowledge and ideas often has the greatest impact on our development.

Over these next 12-weeks, you will embark on a bespoke program of self-directed study at the edge of your abilities. In Stochastic Studio, you’re primarily accountable to yourself. You’re setting your own goals, working and learning at the pace that works for you, and following your curiosity. You’re strengthening one of the fundamental skills of successful venture scientists – autodidacticism.

The most important thing you’ll do in Stochastic Studio is push yourself as a venture scientist. You will pick projects you are passionate about that are at the edge of your abilities, and work on them either alone or with others. You’ll reflect on your goals and progress, go down rabbit holes, and learn things that you did not expect to learn.

About every two-weeks we will have a live session, during which you will share your work, give feedback on the other projects presented, and engage in interactive experiences that will improve your autodidacticism. Our sessions will evolve alongside works-in-progress.

Course Goal

By the end of this course, you will be able to maximize limited resources to self-direct your own learning while making giant leaps in your personal development as a venture scientist.

Course Project

At the start of the term you will each be given USD $1,000...your challenge is to use this money to maximize your development by working on any project that you believe will most benefit you as a venture scientist (all receipts must be submitted to VSD). This might be developing a business focused project, a technical project, a project that helps you develop healthy lifestyle habits, etc.

The only requirement is that your project must revolve around creating something that is specific and measurable, and the process of creating must make the biggest possible contribution toward your personal growth as a venture scientist (within the constraints of time and money). This could be a publication, the creation of a simple prototype (digital, physical, biological, etc.), a live presentation, a remix of a scientific product, a data model, etc.

This course will introduce you to Scoping, a process of working backwards from a desired societal outcome to improve your understanding of the possible ways to achieve that outcome. You will learn the basics of scoping, characterise outcomes, decompose problems, and mapping the relevant technoscientific landscape. As you progress, you will engage with scoping moves, prioritisation criteria, and discover your personal opportunity areas you will be focusing on during your PhD. The course culminates in generating a long list of approaches ranked by their upside, neglect, and tractability.

Course Goal

The course aims to equip you with the skills needed to generate, assess, prioritise, and propose innovative solutions in a creative and first-principled way.

Course Project

All the milestones in this course build toward the end of the term project where you will assess and rank your approaches for your venture creation endeavour.  You will prepare a presentation that effectively showcases the proposed approaches while providing a clear and convincing justification. Each approach should clearly articulate its reasoning chain, explicitly explaining how it connects to the high-level outcome and the quantified outcomes or sub-outcomes you have identified.

“The literature” is cited as a source of truth across all technical domains. Standardised approaches to aggregating and critically reading academic literature will encourage a common intellectual language you can speak across academic fields. In this course you will gain fluency in interview techniques that serve their rapid communication with a diverse community of academic and industry experts. Your path to galvanising collective action begins here, listening to the collective and sense-making to build a broad understanding of technologies and business models in the sector from status quo to state of the art.

This course is an asynchronous complement to Intro to Scoping. You will learn how to dig deep into doing a wide variety of secondary research as you progress through your scoping process.

Course Goal

Same as Intro to Scoping

Course Project

Same as Intro to Scoping

One of the best ways to understand customer needs, check your assumptions, and overcome the tendency towards self-referential design, is to conduct customer discovery research before you build a product or service.

This customer discovery course will help you develop the necessary skills and practice setting up research efforts to understand needs of your target customers, get familiar with a sense of ambiguity, and compare what people say they do to what actually happens.

Course Goal

By the end of this course, you will be able to design and conduct customer discovery research to produce insights that inform the development of your science ventures products and services. Our course goal is to bridge the gap between your ideas as the founder and your customers, theoretical knowledge of different customer discovery research methods and practical application, ensuring that you can apply your customer discovery research skills effectively in real-world scenarios as you will be recruiting your potential customers and getting primary data for your venture.

Course Project

One of the most exciting aspects of this course is that it will culminate in a customer discovery exhibition. You will not only gather qualitative data through your research but also transform your findings into tangible and visual representations. This exhibition will showcase your in-depth understanding of your customers and the insights you have gained through your research. It will be a platform for you to present your updated personas and journey maps based on your findings.

In this course you will learn about the inner workings of technoeconomic analyses and their importance in scaling technologies. The course features six milestones that will introduce the central tenets of building a successful and robust technoeconomic model. You will explore the critical outcomes of a technoeconomic analysis, including operating costs, capital expenses, and financial forecasts, and how to generate these outcomes through process modeling. The culmination of the course will be a complete technoeconomic report and a presentation that outlines the important findings from each participants work.

Course Goal

The goal of this course is to develop an example technoeconomic model for each participant to evaluate ideas in their opportunity area through economic evaluation and case studies. Through this process, participants will gain a deeper understanding of their technology and have a defined roadmap for creating an economically viable product.

Course Project

Over the 12 weeks of this term, you will create a technoeconomic model that can be used throughout the programme to evaluate the economics of your product/process. The project will begin with a literature review and market research to understand existing information in the context of a TEA. Through the development of the model you will gain an understanding of the operating expenses and capital needed for your technology and be able to communicate these effectively through a user-friendly faceplate. The project will culminate in a roadmapping session as well as a slide deck to pitch investors or board members about the findings from your model. It is essential the materials from the milestone are used to highlight the value the model brings to your company and process/product.

To develop the ability to lead in uncertain environments, participants will utilize pragmatic interview techniques to access the judgement, expert knowledge, and intuition of successful deep tech entrepreneurs.

The Applied Cognitive Task Analysis methods are highly rigorous, and are used by academics and practitioners throughout the world and across industries.

Through this course you will gain a deeper understanding of the processes that influence the choice and behaviour of entrepreneurial thinking and to better understand how expert judgements and decisions can shape science ventures in uncertain times.

Participants will be encouraged to examine how the characteristics of the decision-maker and the immediate environment can help or hinder judgements and decisions, and to develop an informed understanding of the ability of successful deep tech entrepreneurs, including themselves, to make decisions.

Course Goal

By the end of this course, you will be able to recognise the cognitive skills in yourselves and others that differentiate highly skilled performance from journeyman levels of performance. You will do this by eliciting knowledge (both explicit and tacit) from recognised skilled performers in the world of deep tech entrepreneurship.

Course Project

By completing a series of Applied Cognitive Task Analysis interviews with deep tech entrepreneurs you will work towards the creation of a new book called "Venture Science". This will be a collaborative output that consolidates all students' work, and culminates in a “book launch party” during our in-person London intensive. Copies of the book will be printed and shared with all experts students have interviewed, the Deep Science Ventures community, and future Venture Science Doctorate students in order to provide insights into venture science expertise.

Concise, compelling storytelling is a powerful tool for enhancing personal performance, sense-making of scientific datasets inspiring collective action, and effectively conveying the value of your science venture. Contextualising and communicating the overarching mission, the hypotheses and the results will make our venture scientists charismatic and coachable. Graduates will use their words and visual design wisely to bring key stakeholders into their venture creation story, and together they will bring the story to life. This course will focus on the cutting edge of praxis in narrative design & storytelling.

Course Goal

By the end of this course, you will have developed a full brand experience for your science venture to engage key stakeholders with. This will include your brand statements, visual identity, information visualizations, fundraising narrative, a visualization of your products value proposition, and a final way to tie all these elements together in a full brand experience (usually a website).

Course Project

Throughout this 12-week period you will work with a number of different designers and contractors to develop all of the initial Narrative elements to effectively tell your science ventures story. Everything that you develop throughout this course will build on each other, and eventually culminate into a full brand experience that you will be presenting to a panel of representative stakeholders for your science venture. We will be using a human factors method called a “desirability study” with these stakeholders. This will be used to determine the effectiveness of your brand experience in connecting with your audience, and also your success in this course.

Business modelling is a core capability that can greatly help deep tech founders in building a successful business. Being able to deploy resources in a way that aligns with the business strategy enables the founder to run efficiently and achieve their business goals quicker.

This course will take a one-two step approach to learning business modelling. First, participants will create their business strategy through the lean canvas approach. This will require taking pen to paper and laying out the customer segments, revenue streams, unique value proposition, cost structure, etc. Second, participants will build a financial model in Excel to project out revenues, costs, financing needs, and more for the next five years. This is an iterative process and at each milestone, participants are expected to fine-tune their assumptions.

Strong business modelling adds rigour to a startup and gives potential investors increased confidence in the founder. While founders may end up hiring a CFO as the business grows larger, it will remain a core job of the founder to deploy resources efficiently and steer the business financially. This course aims to equip founders with this necessary skill.

Course Goal

By the end of this course, you will be able to create a Lean Canvas and financial model for your deep tech startup. Through this work, you will be able to evaluate what revenues, resources, and financing are necessary to grow your startup.

Course Project

Over this term, you will first create a Lean Canvas for your startup (Milestones 1+2), which will then help you create a robust financial model in Excel for your startup (Milestones 3 through 6). You can choose from two Excel templates for your financial model:

1. A subscription-based financial model for startups aiming to sell recurring subscriptions to consumers (B2C) or businesses (B2B)

2. A product-based financial model for startups aiming to sell various products on a one-off basis at various prices.

This template Excel model will guide you through building out market information, revenue projections, resource and cost needs, financial statements, financing needs, valuation, and various scenarios. This financial model can be a starting point for managing your business and speaking with investors.

The aim of this course is to guide PhD candidates through the process of strategic experimental design to accelerate the journey from hypothesis to market-readiness. It aims to bridge the gap between performing a valid experiment and crafting a set of strategically selected experiments that lead to the shortest and most impactful path to market success.

The course is scaffolded to guide you on how to connect standard experimental validation with a series of optimised experiments that consider risk, potential for upside, and the necessity to hit critical milestones efficiently. This is achieved by first identifying the major value inflection points relevant to the approach’s ultimate goal. You will then learn to reverse-engineer the trajectory from these points: work backwards to what Milestones are needed to prove concept, then work backwards from that to the optimal set of experiments to reach those milestones (accounting for risk, funding and cost-value of time). As you build your experimental plan, the course places an emphasis on creating an execution strategy centered around a core set of 'critical path' experiments.

In Experience design you will experience the following:

• You will have bi-weekly one-to-one meetings with a DSV supervisor

• You will have bi-weekly one-to-one meetings with an external technical supervisor

• You will attend all weekly All-Hands meetings with the whole DSV community to engage with Founders-in-Residence that are presenting their work

• And you will present your own Experiment Design work at select All-Hands meetings

Course Goal

This course aims to bridge the gap between performing valid experiments and strategically selecting those that lead to the shortest, most impactful path to your approaches’ market success, by emphasising potential upside, and critical experimental milestone derisking.

Course Project

Your course project will be split into six project milestones designed to incrementally build and refine your strategic experimental plan. This plan aims to minimise risks, enhance clarity from initial experiments, and position your research for successful execution as you go into year 2.

This module prepares a student to contribute new knowledge to scholarship in a specific deeptech sector, such that they can conduct (in subsequent modules) a programme of original, publishable research that advances the state of knowledge in their chosen field.

The main goal of this module is the completion of a Research Plan. The module prepares students to embark upon a substantial, sustained, unified piece of research at the MQF 8 level. The module is taught by the proposed thesis supervisor as a form of preparation specific to the thesis and the requirements of its subject matter. The thesis supervisor must possess a research doctorate in the field and sub-field of the proposed dissertation, or failing that, recent peer-reviewed scholarship in that area that demonstrates academic expertise. Approval of the match between a doctoral student and supervisor will rest with the dean of the college, and must be reported to Woolf’s QAETAC committee.

This module is not a general introduction to research or research methodologies, but a practical preparation for students preparing to embark upon the thesis. Although these skills are highly transferable to other research domains, it remains the case that the purpose of the module is scoped to the needs of the specific thesis for which it prepares the student.

The module results in a highly structured ‘Research Plan’ for embarking upon independent research at the MQF 8 level in the subsequent modules.

In order to provide context for the submission of the ‘Research Plan’ (which is the purpose of this phase of the module), the student will gain a proficient knowledge of relevant research methods and planning. Thus, in connection with the core learning outcomes resulting from the research plan, the student will additionally gain a proficient understanding of the wider context of research methods and evaluate the fittingness of the chosen method.

In this phase a student must, under the guidance of their supervisor:

1. Propose his or her thesis topic

2. Identify a provisional title

3. Evaluate research methods and select a strategy

4. Write an abstract of the proposed research

5. Compose a provisional table of contents for the thesis

6. Compose an annotated bibliography

7. Write a literature survey covering the primary and secondary sources

8. Schedule a timeline to completion, including a work agreement that establishes mutually-agreed upon expectations with the supervisor for meetings, responses to student work, and any other relevant practices.

The thesis supervisor finally prepares the student for external examination of the ‘Research Plan’.

By the end of the first year, if not earlier, the Research Plan is submitted as a digital portfolio containing six elements:

1. Provisional thesis title

2. Abstract

3. Expanded table of contents

4. Literature survey

5. Annotated bibliography

6. Timeline to completion

The Research Plan provides students with a clear framework to guide their research question, a structure into which they can fit their scholarly research, and a pathway to the completion of the thesis. The Research Plan also formally specifies the discipline the student is studying; this discipline must also be the supervisor’s scholarly field. During the module, students meet with their supervisor twice per month.

The student’s attention is directed to literature on the topic of the proposed thesis, and thus methodological research guidance, beyond the oral instruction of the student’s supervisor, will be provided within the domain of study specific to the student’s thesis. This will vary considerably, depending upon the topic of the thesis, and it forms a natural component of the literature survey. Within Venture Science, the literature survey will also include a Sector Architecture, which articulates the successes and failures of academic research in a specific field with commercial, industrial, and financial factors. (Thus, it is neither appropriate nor possible to list here the bibliographic references that will be needed by the student. We have, however, provided valuable works of general research guidance and reference, and works to aid the student in evaluating the best research method for the thesis.) Although the nature of the training will vary by discipline and by the focus on human subjects, the supervisor will include scholarly ethics as a topic during this period.

The ‘Research Plan’ is submitted to be examined by an academic in the same field, selected by the thesis supervisor with the approval of the college dean (for the role of college deans, see Woolf’s MFHEA-approved Policy of Quality Assurance). The examining academic must possess a research doctorate.

Advanced Research Progress and Progress Review helps a student who has just completed the ‘Research Plan’ to undertake a cadence of supervised, original research leading to a substantial portion of their research thesis being completed (2-4 chapters or equivalent).

Although students may request twice-weekly meetings early in the writing process, it is expected (and students typically prefer) not to meet more than twice per month thereafter. This allows the student time to develop their independent research and writing. As the student advances in independence and confidence in their research, and under the discretion of their supervisor, they may reduce their supervisory meetings to 1 time per month, though they must continue to participate in ‘Work in Progress’ seminars each month.

Under the supervision of their supervisor, and through regular submissions and synchronous feedback sessions, students hone and strengthen their ability to conduct innovative, original research at the very forefront of an academic discipline.

While the focus of year one was on preparing the ‘Research Proposal’, the focus of year two is on the actual work of research, whether that be in the library, working with datasets, work in the lab, or deep reading in the scholarship on a chosen topic, producing extensive notes and questions, and rough drafts of chapters or thesis sections.

In addition, supervisors in year two will facilitate the student’s participation in the broader scholarly community, whether through presenting in the ‘Work in Progress’ seminar for graduate students and scholars, or through recommended and invited academic conferences.

Entering the third year of doctoral studies, students will have a well-defined research topic, a clear structure to organise their proposed research, a firm grasp of the relevant literature, a practical timeline in which to conduct their research, and a substantial body of drafted thesis chapters or sections (equivalent to 2-4 chapters).

In this module, the aims of the methodology module are fulfilled and the research of the past two years is brought into one overarching argument. The exact length of the thesis will vary by method and discipline, but ordinarily will not exceed 80,00-100,000 words, exclusive of any appendices.

The thesis will constitute a substantial, original, independent piece of research, which is clearly articulated in relation to the primary evidence and secondary literature, and which is organised in relation to the plan first envisaged in the methodology module.

Students may select the Integrated Thesis option for their dissertation, which results in a shorter document drawing directly on publishable or published material. The Integrated Thesis option  will typically be 20-40,000 words (not longer than 80,000 words without express permission from Woolf), exclusive of appendices and data sets. A doctoral thesis on the Integrated Thesis option may be accepted for examination if it consists of a minimum of three papers of publishable quality, framed by an introduction, a literature survey (either written as a stand-alone chapter or divided among the constituent chapters), and a conclusion. The thesis must represent a contextualized and broadly coherent body work, justified in the introduction and conclusion. At least one  paper must be authored solely by the candidate. Any co-authored papers must include a statement describing the candidate’s contribution to the paper. Where the co-author is another student at Woolf who also intends to include the paper in their own thesis, permission to include the paper must be approved, prior to submission for examination, by the Academic Board of the college, with written notice to Woolf’s Quality Assurance, Enhancement, and Alignment Committee (QAETAC).

Regular supervision meetings keep the student on-course with the timeline agreed in the methodology module. Supervisory meetings concentrate on a pre-submitted piece of research in a pattern that continues until the first draft of the thesis is complete.

Although students may request twice-weekly meetings early in the writing process in module two, it is expected (and students typically prefer) not to meet more than once or twice per month by this stage of the thesis. This allows the student time to develop their independent research and writing.

All full-time students must meet with their supervisor at least once per month. Students meeting only once a month must also participate each month in Works-in-Progress seminars.

After the completion of the first draft, meetings focus on the harmonisation of the parts, adjustments to the overall argument, and the supervisor seeks to ensure that the student guides the thesis with a single, coherent line of enquiry.

The final meetings with the student focus on polishing the editorial aspects of the thesis, and helping the student prepare for examination.

While there is not a formal requirement that a piece of the thesis will have been published already, the thesis should contain publishable work, and the student should graduate with a clear plan of revision toward publication (e.g., a series of articles, direct publication, or recasting the argument as a book for a more general audience).