25 Postdoctoral Fellowship at University of Edinburgh, Scotland, United Kingdom

A two-year Postdoctoral Research Assistant (PDRA) to carry out research into generating Earth System Models that show sub-polar gyre collapse.  The research requires numerical modelling, analysis and publication of results in world class journals. The PDRA should also collaborate with others in Edinburgh and in the PROMOTE (Progressing Earth System Modelling for Tipping Point Early Warning Systems) project. This project brings together researchers from seven UK research institutions and is funded by ARIA (Advanced Research and Invention Agency). 

The PDRA will form part of the PROMOTE project in which UK scientists are developing and using the UK Earth System Model (UKESM) to examine the potential collapse of the North Atlantic sub-polar Gyre circulation. Within this large project the Edinburgh component has the aim of generating a handful of UKESM variants that are less realistic but more sensitive to freshwater fluxes from Greenland ice melt. This will use advanced numerical techniques to calibrate the ocean/sea-ice component of UKESM to agree with North Atlantic observations and produce variants that are differently sensitive to ocean freshwater flux off Greenland. 

The PDRA should contribute to potential follow up bids for funding in the broad area of tipping points or the novel use of inverse methods in ocean or earth system modelling.

This post is full-time (35 hours per week); however, we are open to considering part-time or flexible working patterns. We are also open to considering requests for limited hybrid working (on a non-contractual basis) that combines a mix of remote and regular on-campus working. However, as the job-holder should interact with other researchers they should be on-campus at least three days a week. 

This job post is for a postdoctoral research associate to conduct research on the role of two G-coupled receptors in the progression of difficult-to-treat acute myeloid leukaemia (AML). 

The job holder will need to (i) study the biology of GPR56/GPR97 in leukemic cells (and in normal haematopoietic stem cells as a control), (ii) establish leukaemia cell lines and human iPSCs lacking one or both GPRs, and (iii) study their effects on haematopoietic cell function to identify mechanisms involved in AML progression and chemo-resistance.

The WARSHARE project is investigating how and why digital participation is transforming how individuals and societies (including militaries and states) fight, experience, and understand (perceive, explain, and de/legitimise) warfare. The project will use AI methods to mine and measure online behaviour at scale, across multiple modes of communication (messages, images, video, memes and emojis) that shape participation and meaning in warfare.

You will lead and manage a range of individual and collaborative research activities across the WARSHARE project; devise and oversee the research strategy; and, lead the design and management of Work Package 1 (‘Participative war, form and content’) with responsibility for the day-to-day project, budget and research activities.

This Research Associate position will contribute to the ADIA2 project within the IMNS institute at the University of Edinburgh, which is funded by DSTL. The role is subject to DSTL security clearance checks and appointment will be subject to candidates successfully completing these checks as well as right to work in the UK checks.

This role is at Grade UE07 and is available on a fixed-term basis until 31^st March 2028.

A full list of main responsibilities and the knowledge, skills and experience required for the role can be found in the full job description below.

This Research Associate position will contribute to the ADIA2 project within the IMNS institute at the University of Edinburgh, which is funded by DSTL. The role is subject to DSTL security clearance checks and appointment will be subject to candidates successfully completing these checks as well as right to work in the UK checks.

This role is at Grade UE07 and is available on a fixed-term basis until 31^st March 2028.

A full list of main responsibilities and the knowledge, skills and experience required for the role can be found in the full job description below.

We are looking to appoint a Postdoctoral Research Associate to join us in an ambitious and high-impact climate research project funded by the UK’s prestigious new Advanced Research + Invention Agency (ARIA). The PROTECT project (Probabilistic Forecasting of Climate Tipping Points) brings together cutting-edge AI, statistical, and machine learning techniques with climate modelling, aiming to transform our understanding and prediction of climate tipping points.

We welcome candidates with expertise in climate modelling, ideally including experience with General Circulation Models (GCMs), Earth System Models, or related simulation tools. Additional knowledge of statistical methods, Monte Carlo techniques, or ensemble approaches is highly valued.

The post is advertised as full-time. We are open to hybrid working arrangements (on a non-contractual basis), combining on-campus and remote work.

The candidate will contribute to the development of new mechanistic models aiming to dissect the as-yet-elusive link between 3D gene structure and function. The successful candidate will ideally have a good experience with polymer models and coarse-grained molecular simulations, and will have experience or willingness to engage with experimental collaborators in joint projects. The results obtained in this work can be used, among other things, to inform models of transcription in disease, and understand how mutations in chromatin-associated proteins or DNA elements associated with genetic diseases and cancers affect transcription. 

This post is full-time (35 hours per week); however, we are open to considering part-time or flexible working patterns. We are also open to considering requests for hybrid working (on a non-contractual basis) that combines a mix of remote and regular on-campus working.  

The dynamical systems view of turbulence, in which the flow “pinballs” between exact coherent states (ECS), is a promising way to unify our statistical understanding of turbulence with a mechanistic understanding of the complex self-sustaining processes that underpin it. Historically, this approach has been restricted to weakly turbulent flows due to the difficulty of identifying and converging ECS, and this project will seek to use advances in machine learning and automatic differentiation to overcome these barriers. 

A core part of this project is the development and interpretation of state-of-the-art machine learning (ML) models to model and predict high Reynolds number fluid flow. The post-holder will work on a combination of: (1) low order models for high-dimensional flows, e.g. generated via self-supervised learning, to parameterise the inertial manifold; (2) super-resolution/data-assimilation strategies incorporating flow solvers in the loss; (3) development of differentiable code for turbulent simulation of wall-bounded flow. 

There are significant computational resources set aside specifically for the post-holder, along with PI, to train large models (access to a dedicated GPU cluster with >200  A100/H100 cards).  There is scope for a strong candidate to shape the research direction. 

We have recently developed a new method of statistical analysis for the problem of finding the key genes for disease, with exciting pilot results and promising drug targets for rheumatoid arthritis and other autoimmune conditions. The post holder will play a pivotal role in helping us further develop this method and take genetic discoveries forward to inform biomarker identification and validation for predicting progression and response to treatment in people with rheumatoid arthritis using available and newly generated transcriptomic and proteomic data.

This post is an important component of the work programme in Dr Spiliopoulou’s career development fellowship funded by Versus Arthritis and aiming to develop a precision medicine approach for rheumatoid arthritis. The post holder will work closely with Dr Athina Spiliopoulou, Prof Paul McKeigue, and Dr Andrii Iakovliev, and with postdoctoral researchers and students in our team. They will also interact and collaborate with academic, clinical and industry contacts from existing collaborations, including the prediction of response to treatment in rheumatoid arthritis, and with colleagues at the Diabetes Medical Informatics and Epidemiology research group at the Institute of Genetics and Cancer.

We are looking for a researcher to join our group at the Centre for Science at Extreme Conditions (CSEC), belonging to the Institute for Condensed Matter and Complex Systems (ICMCS) of the University of Edinburgh. 

The appointed Postdoctoral Research Associate (PDRA) will utilise the laser-heated diamond anvil cell approach to synthesise novel and technologically relevant nitrogen-based materials. The PDRA will employ the newly-developed single-crystal X-ray diffraction of powder-like samples for the structural characterisation of nitrides, along with Raman spectroscopy measurements. This programme of research will be conducted in collaboration with researchers from the University of Bayreuth (Germany), the Commissariat à l’Énergie Atomique (France) as well as the University of Linköping (Sweden) and has been funded by the UKRI through a Future Leaders Fellowship (FLF).

(18) Postdoctoral Fellowship Position

Postdoc Fellowship Position summary/title: Research Associate in AI for Electronics Testing & Verification automation

Deadline : 07/10/2025,

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