UROP - Available Projects
PDF versionThe UROP is designed to support undergraduates studying at the University of Cambridge who are going to return for at least one more year of undergraduate study.
Final year undergraduates and postgraduate students should not apply.
Some projects with external funding have additional restrictions, such as those funded by EPSRC.
If you have any questions please contact Joe Goddard, Industrial Placements Coordinator, who administers UROP projects for the Department of Engineering.
Further information can be found below:
Available Projects
Transonic wind tunnel experiments for low-drag aero-engine intakes under crosswind conditions
Primary Supervisor Details
Name: Luke Dickinson, ld599@cam.ac.uk
Industrial Collaborator
Edward Jinks, Siemens
Project Description
Future aviation decarbonisation targets require substantial improvements in turbofan propulsive efficiency. Ultra-high bypass ratio engine architectures aim to achieve this by reducing fan pressure ratio, increasing propulsive efficiency and lowering fuel burn. However, maintaining thrust with lower fan pressure ratios requires larger fan diameters and nacelles. To avoid a cruise, drag penalty from increased nacelle wetted area, future intakes must become shorter and more aerodynamically aggressive.
These aggressive intake geometries are more susceptible to boundary-layer separation during off- design operation, particularly under crosswind conditions during take-off and climb. In this regime, the windward engine ingests crossflow which must negotiate a strongly curved intake surface, producing adverse pressure gradients, transonic shock–boundary-layer interaction and possible flow separation. This can generate stagnation pressure loss and fan-face distortion, reducing compressor stability margin, engine operability and overall performance. The unmet need is both aerodynamic and industrial. For companies such as Siemens, there is continued economic interest in improving the predictive capability of industrial CFD tools for this difficult flow class: high-Reynolds-number, transonic, curved-surface shock–boundary-layer interaction with incipient separation. Current numerical methods are widely used to guide aerodynamic design, but their reliability depends on validation against representative experimental data. At present, there is limited high quality experimental data for sharp intake geometries under crosswind-relevant transonic conditions, which creates uncertainty in CFD-driven design decisions and increases the risk of costly late-stage redesign.
This project will build on an existing experimental rig at the Cambridge University Engineering Department transonic wind tunnel facility that reproduces representative crosswind intake flow conditions. A summer UROP student will investigate simple passive boundary-layer control concepts, including surface roughness and low-profile vortex generators, to delay or suppress separation. The project will generate targeted validation data and design insight to help Siemens assess and tune CFD modelling approaches, de-risk future aerodynamic design studies, and support progression of passive flow-control concepts from early proof-of-principle towards higher TRL development and future collaborative projects.
Essential Knowledge, Skills, and Attributes
Proficiency in CAD and MATLAB/Python. Wind tunnel experimental experience would be a bonus.
Timing
- Application closing date: Rolling review (nominally end of term)
- Project start and end dates: 6th July 2026 – 28th August 2026
Continuation Opportunities
Fourth-year projects run every year in the transonic wind tunnel, so this UROP would provide excellent preparation for a potential follow-on MEng project.
Application Details
Name and email of the person receiving the applications: Luke Dickinson – ld599@cam.ac.uk
Deadline for applications
Rolling review (nominally end of term)
The Centre for Science, Technology and Innovation Policy (CSTI) at the IfM has four summer project opportunities for students. If any of the projects sound interesting and you think you may have the right expertise, please send your CV with a cover email to Eoin O’Sullivan and Viktoria Doeme at eo252@cam.ac.uk and vd334@cam.ac.uk. The precise timing, duration and part-/full-time arrangement are flexible, to be agreed with the candidate.
Deadline for applications: midnight 14 June
Interviews: week of 15 June
Project 1: Aligning and integrating strategic foresight analysis of emerging technologies (general call)
In collaboration with the UK Department for Science, Innovation and Technology (DSIT), the Centre for Science, Technology and Innovation Policy (CSTI) has developed a methodology for strategic analysis of emerging technologies published in a policy handbook.
The methodology is made up of several key steps that enable more systematic and effective analysis for strategic thinking and foresight. This includes:
- mapping technology/ies and standardizing terminology (tested on quantum sensing, composite materials, and robotics),
- roadmapping the innovation pathway of selected technology/ies to understand barriers and opportunities along the pathway, and
- identifying current strengths, weaknesses and benchmarking internationally, including via bibliometric and patent analysis.
These steps can be used flexibly, but they were designed in a way that they are interlinked and can feed into each other.
This project will build on the already developed methodology by testing and improving its steps separately or in combination. The project scope will involve a more narrowly defined emerging technology use case. Potential use cases of interest include quantum sensing, quantum photonic integrated circuits, metamaterials but we are open to other emerging technologies that might be of interest to you as well.
Please clearly specify your emerging technology interest and expertise in your cover letter. Technical expertise and/or understanding is highly desirable.
Previous experience working on strategic foresight analysis or workshop convening is an advantage.
The project duration will be up to 8 weeks; both full-time and part-time arrangements will be considered. The precise timings are to be agreed with the successful candidate.
To apply, please send your CV with a cover email to Dr. Eoin O’Sullivan and Dr. Viktoria Doeme at eo252@cam.ac.uk and vd334@cam.ac.uk the latest by midnight on 14 June 2025.
Project 2: Aligning and integrating strategic foresight analysis of emerging technologies (Quantum Sensing focus)
In collaboration with the UK Department for Science, Innovation and Technology (DSIT), the Centre for Science, Technology and Innovation Policy (CSTI) has developed a methodology for strategic analysis of emerging technologies, published in a policy handbook.
The methodology is made up of several key steps that enable more systematic and effective analysis for strategic thinking and foresight. This includes:
- mapping technology/ies and standardizing terminology (with initial testing already undertaken for quantum sensing),
- roadmapping the innovation pathway of selected technology/ies to understand barriers and opportunities along the pathway, and
- identifying current strengths, weaknesses and benchmarking internationally, including via bibliometric and patent analysis.
These steps can be used flexibly, but they were designed in a way that they are interlinked and can feed into each other.
This project will build on the already developed methodology by testing and improving its steps separately or in combination, with a specific focus on quantum sensing as the emerging technology use case. The project will leverage initial analysis already conducted on technology mapping for quantum sensors and further develop this work across the remaining stages of the methodology.
The project scope will therefore involve a more narrowly defined quantum sensing use case, including refinement of terminology, deeper analysis of innovation pathways, and strengthened international benchmarking.
Please clearly specify your expertise and interest in quantum sensing in your cover letter. Technical expertise and/or understanding is required.
Previous experience working on strategic foresight analysis or workshop convening is an advantage.
The project duration will be up to 8 weeks; both full-time and part-time arrangements will be considered. The precise timings are to be agreed with the successful candidate.
To apply, please send your CV with a cover email to Dr. Eoin O’Sullivan and Dr. Viktoria Doeme at eo252@cam.ac.uk and vd334@cam.ac.uk the latest by midnight on 14 June 2025.
Project 3: Aligning and integrating strategic foresight analysis of emerging technologies (Metamaterials focus)
In collaboration with the UK Department for Science, Innovation and Technology (DSIT), the Centre for Science, Technology and Innovation Policy (CSTI) has developed a methodology for strategic analysis of emerging technologies published in a policy handbook.
The methodology is made up of several key steps that enable more systematic and effective analysis for strategic thinking and foresight. This includes:
- mapping technology/ies and standardizing terminology (tested on quantum sensing, composite materials, and robotics),
- roadmapping the innovation pathway of selected technology/ies to understand barriers and opportunities along the pathway, and
- identifying current strengths, weaknesses and benchmarking internationally, including via bibliometric and patent analysis.
These steps can be used flexibly, but they were designed in a way that they are interlinked and can feed into each other.
This project will build on the already developed methodology by testing and improving its steps separately or in combination. The project scope will involve a more narrowly defined emerging technology use case, with a specific focus on metamaterials.
Within this focus, particular areas of interest include, but are not limited to:
- Reconfigurable Intelligent Surfaces (RIS) – understanding the UK and international landscape of how this technology is being progressed to manufacturing and market readiness. Taking a systems thinking/engineering perspective, the analysis would consider the supply and value chain, including specific enablers, the controllable materials, the control systems required, and the practicalities of obtaining and producing them. This may extend to consideration of product and product development lifecycles and how these influence scalability and adoption.
- Increasing productivity of manufacturing process lines through, for example, adoption of inline process control, enabled for example by metamaterial-enabled compressive sensing or imaging capability. This would involve translating technical advantages into forecast economic or other benefit measures.
The project will apply the CSTI methodology to this use case, including technology mapping and terminology development, innovation pathway analysis, and international benchmarking.
Please clearly specify your interest and expertise in metamaterials in your cover letter. Technical expertise and/or understanding is required.
Previous experience working on strategic foresight analysis or workshop convening is an advantage.
The project duration will be up to 8 weeks; both full-time and part-time arrangements will be considered. The precise timings are to be agreed with the successful candidate.
To apply, please send your CV with a cover email to Dr. Eoin O’Sullivan and Dr. Viktoria Doeme at eo252@cam.ac.uk and vd334@cam.ac.uk the latest by midnight on 14 June 2025.
Project 4: Analysis of government procurement approaches for emerging technologies
In relation to ongoing work on emerging technology policy and government procurement, the Centre for Science, Technology and Innovation Policy (CSTI) is exploring how government procurement mechanisms can support the development and scale-up of emerging technologies. In particular, this project will examine and compare the strategies underpinning programmes such as the US Small Business Innovation Research (SBIR) programme and the UK Small Business Research Initiative (SBRI).
The project will contribute to a wider discussion on the role of public procurement in shaping emerging technology ecosystems, using SBIR and SBRI as exemplar case studies. Key questions of interest include whether the strategic objectives and implementation approaches of these programmes differ, how procurement processes are structured, and whether they support different types of technologies (e.g. end-products, core technologies, or enabling tools).
The project could involve some or all of the below interlinked components:
- A literature review of existing government procurement programmes for emerging technologies, identifying key design features, objectives, and policy rationales.
- A comparative analysis of SBIR and SBRI, including how calls are designed, procured, and evaluated.
- Analysis of SBIR and SBRI project awarded data, identifying patterns in technology focus, sectoral distribution, and types of supported innovation.
- Development and testing of a Natural Language Processing (NLP)-based methodology that could be applied to similar datasets in future analyses.
Optional to focus on specific emerging technology or sector (e.g. engineering biology, quantum technology or other areas) for analysis of SBRI and SBIR, depending on candidates interest and expertise.
This project will build methodological capability while generating insights into how procurement can be used as a strategic tool to support innovation and emerging technologies.
Please clearly specify your expertise and interest in your cover letter. Backgrounds in engineering, Manufacturing Engineering Tripos (MET), data science, or related fields are highly desirable. Experience with NLP methods or data analysis would be an advantage.
Previous experience working on policy analysis, emerging technologies, or innovation systems is also beneficial.
The project duration will be up to 8 weeks; both full-time and part-time arrangements will be considered. The precise timings are to be agreed with the successful candidate.
To apply, please send your CV with a cover email to Dr. Eoin O’Sullivan and Dr. Viktoria Doeme at eo252@cam.ac.uk and vd334@cam.ac.uk the latest by midnight on 14 June 2025.
Bilt - novel low order physical systems modelling tool
Primary Supervisor Details
James Emberton, Aviation Impact Accelerator, Whittle Lab, Dept of Engineering
Project Description
Bilt is a novel low order computational modelling tool. We are developing a completely novel approach to support analysis of complex physical systems, in an accessible way, based on functional programming principles. This project is based at the Aviation Impact Accelerator at the Whittle Lab and supports work to de-carbonise aviation. However, we anticipate that the Bilt tool can be applied more generally in the world of systems modelling.
A number of potential projects are available depending on the student's skills and interests. These could include:
- design and evaluation of novel computational and static analysis infrastructure
- prototyping new physical systems toolboxes
- developing cloud compute and data workflows
This is an opportunity to help shape the future of a novel open-source computational tool with enormous potential.
Essential Knowledge, Skills, and Attributes
All projects require strong familiarity with Python as a minimum and a strong interest in sustainable aviation.
Depending on the project the following skills may be useful:
- Programming languages such as Rust, OCaml, or Haskell
- Knowledge of computational graphs, compilers, computer algebra, or functional programming
- Array computation (e.g. JAX), compiler infrastructure (e.g. LLVM), or symbolic mathematics (e.g. CasADi)
- A background in Chemical, Mechanical, Electrical, Aerothermal Engineering or Computer Science
- Interest in open-source software development
Timing
Applications will be assessed on a rolling basis
Any applicants will be expected to start their 8–12-week placement in July
Continuation Opportunities
There is potential to support continuation work for undergraduate thesis or MSc projects.
Supporting Information
Application Details
If you would like to apply, please send your CV and a short cover letter to Anna Petrosyan, ap2522@cam.ac.uk.
Last updated on 03/06/2026 09:56