University of York

Below is a list of prospective projects you can apply for, complete with a short explanation and the lead supervisor's name and department. Please contact them before making your application; you will be asked if you have done this on the application form.

If you are interested to learn more about a specific project before applying, download the full project proposal at the bottom of the page.

Optimising MPI_Alltoallv for 3D FFTs. Steven Wright, Computer Science

This summer internship aims to optimise the performance of distributed 3D Fast Fourier Transforms, with a particular focus on scientific computing applications. One of the dominant operations in distributed 3D FFTs is the MPI_Alltoall collective operation. Research has demonstrated significant latency reductions for uniform large-message Alltoall communications on Exascale systems. However, applications such as CASTEP often rely heavily on the Alltoallv variant, where processors exchange variable amounts of data. This project is focused on adapting state-of-the-art algorithms to Alltoallv.

Designing and implementing a data pipeline and data warehouse to store and visualize air quality instrumentation data. Stuart Lacey, IT Services

This project aims to advance the Research Data Management strategy at the Wolfson Atmospheric Chemistry Laboratories by developing a scalable, automated pipeline for heterogeneous instrumental data. By leveraging HPC resources, raw datasets will be processed into a structured architecture stored across on-premises and cloud environments. This hybrid system integrates SQL querying and real-time dashboards, facilitating rapid data retrieval for researchers and proactive telemetry for instrument maintenance.

Mapping in situ immune microenvironments from skin lesions of early controlled human challenge to chronic field infections using spatial transcriptomics Nidhi Sharma Dey, Biology

Cutaneous leishmaniasis causes diverse skin pathology globally. Human challenge models study early infection but fidelity to natural disease remains un-validated. This project leverages a spatial Visium transcriptomics resource spanning challenge infections and field lesions from four global cohorts to compare immune microenvironments across Leishmania species and presentations. Using HPC, the student will perform deconvolution, trajectory analysis, pathway enrichment, and cell-cell communication inference, culminating in an open-access R Shiny community resource.

Genetic insights into the cultivation history of poppy Surabhi Ranavat, Archaeology

The domestication history of the opium poppy is a major question for archaeologists, botanists and the medical community. Ancient DNA research provides a way to explore the human past using genomic sequencing data. Here, DNA from poppy accessions will be used to explore the pace of domestication and its use for humans in the past. During this internship, data from poppy specimens will be processed with a bioinformatic pipeline for archaeological crops. The wider goal of this project is to set the foundation for expanded analysis of ancient poppy specimens that are being processed in York.

High-Performance Proteomics at Scale: An R Package and Interactive Web Portal for Standardised Analysis William Grey, Biology

Existing proteomics analysis tools do not support batch correction, machine learning (ML) or modelling. Essential when samples span multiple experimental runs, timepoints or patient donors. We have developed pipelines to fill this gap, broadly applicable across DIA and DDA datasets, covering quality control, batch correction, differential expression and ML (pseudotime, KSEA, LASSO regression and random forest classification). The student will formalise an HPC-ready package for large-scale datasets, and an interactive web portal for smaller cohorts gaining experience in research software engineering, HPC, and ML for biological data.

If you designed a project with a supervisor, please complete the application form with your project title.

This is what is required to complete the application form.

1. Your details
2. Answers under the following three headings (max 2000 characters each):

• Degree course and interest in the subject
• Motivation for applying for an N8 CIR internship
• What I hope to gain from completing the internship

1. An uploaded CV including the contact details of one referee (no more than 1 page)

Your uploaded file should be named: "YourSurname_initials_York.pdf" e.g., Other_AN_York.pdf

If you are having problems with your application, please contact us at enquiries@n8cir.org.uk

Applications will be assessed by a panel at the university and successful students informed by email if they will be offered the internship.

Application deadline: 13 April, 2026

Successful students notified: before 24 April, 2026