The Tollervey lab seeks to understand the nuclear pathways that synthesize and process newly transcribed RNAs, the assembly of RNA-protein complexes and the surveillance activities that monitor their fidelity. To achieve these goals, we have developed a range of high-throughput techniques for mapping RNA-protein, RNA-RNA and RNA-DNA interactions. 

In particular, we are analyzing the role of RNA-DNA hybrids (R-loops) in gene expression and DNA replication, and the roles of RNase H and RNA surveillance pathways in their clearance. The project will involve the development and application of techniques to analyze high-throughput sequence data and, potentially, proteomic data. This position is funded by the Leverhulme Trust and is available for 2 years. 

We are looking for an enthusiastic individual to join our thriving bioinformatics public engagement programme, 4273pi (https://4273pi.org), as Postdoctoral Research Associate in Bioinformatics Education. The post involves designing, planning, delivering and researching public engagement with secondary schools across Scotland.

This post is advertised as part-time (17.5 hours per week), however, we are open to considering other working patterns.

We are looking for a Post-Doctoral Research Associate to lead a project on the valorisation of polyester-derived terephthalic acid into high value flavour and fragrance molecules using strain engineering and biocompatible chemistry. The project will be based in the lab of Dr Joanna Sadler in the Institute of Quantitative Biology, Biochemistry and Biotechnology (IQB3).

We are looking for a highly motivated Postdoctoral Research Fellow to join the laboratory of Sebastian Greiss at the Centre for Discovery Brain Sciences, University of Edinburgh. The successful candidate will conduct original research at the intersection of synthetic biology and neurobiology, developing and applying state of the art in vivo tools in C. elegans. 

We are looking for a postdoctoral researcher to develop novel stem cell gene therapies for childhood neurological diseases. Your main role will be to develop and improve ex vivo stem cell gene therapies for Mucopolysaccharide diseases. Experience of working with mouse disease models and gene or cell therapy is essential.

This post is advertised as full-time (35 hours per week); however, we are open to considering part-time or flexible working patterns. 

We are looking to hire a highly motivated Research Fellow in Food Systems Thinking (Analytical Support), with excellent analytical, organisational and interpersonal skills, to work on our new Wellcome Trust Living Good Food Nation Lab project (https://wellcome.org/grant-funding/people-and-projects/grants-awarded/building-health-centred-net-zero-aligned-food). 

This project is closely linked to exciting new Scottish legislation, the Good Food Nation (Scotland) Act, and aims to support its ongoing implementation. Led by University of Edinburgh Business School, our transdisciplinary team brings together academic, governmental, public sector and 3^rd sector partners with expertise in nutrition and public health, environmental modelling, public food procurement, food policy and governance, anthropology, and sociology, of food, food and procurement law, social policy, behavioural change, and food systems transformation. 

This post is advertised as fixed term (36 months) and full-time (35 hours per week) however, we are open to considering part-time (4-5 days) and/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 with a minimum requirement for 2 days/week on campus working.

A postdoc is required for a multidisciplinary research group (Dr Selvaraj/ Prof Wishart /Prof Chandran) within the UK Dementia Research Institute to contribute and expand our knowledge on pathophysiology of motor neuron disease (MND) with an ultimate goal of developing novel therapeutics and development to clinical trial. In particular, this project will investigate cellular dysfunction in motor neurons and role of glial cells in modulating motor neuron function in MND using various patient derived 2D human stem cell models. This project will also involve in testing high value candidate drugs that emerge from ongoing drug discovery projects in Edinburgh. The post holder will conduct original research and produce data for high quality publications, grant proposals and dissemination to the public. 

A postdoc is required for 12 months to contribute to innovative research into understanding the role of glial cells is Parkinson’s disease in a collaborative project (Prof Chandran, Prof Dario Alessi -MRC-PPU Dundee) group within the UK Dementia Research Institute, planning and conducting experiments, analysing and interpreting data. The postdoc will take a lead in the dissemination of their own findings via academic publications and presentations, as well as involving and engaging the public.

A postdoc is required for 12 months to contribute to innovative research understanding the role of neuromuscular junction degeneration in motor neuron disease using human stem cell organoid in a multidisciplinary research group (Dr Selvaraj / Prof Chandran) within the UK Dementia Research Institute, planning and conducting experiments, analysing and interpreting data. To take a lead in the dissemination of own findings via academic publications and presentations, as well as involving and engaging the public.

The post is full-time (35 hours per week) and fixed term for 2 years. It is possible to extend as per performance and further discussion.

The successful candidate will be supervised by Dr. Changjian Li and Dr. Laura Sevilla-Lara (with a dotted line to Prof. Melissa Terras). In collaboration with other researchers at Abertay University, the team will study generative AI methods to design new machine learning systems to enhance the current workflows of the creative industry, from content creation (2D and 3D), exploration to use (animation, simulation). The successful candidate will also have the opportunity to work with world-leading industry partners in gaming, animation and film sectors by discovering new research topics, developing thoughtful integration of generative AI into virtual production and performance pipelines, and accessing real industrial data as a unique advantage.

The School of Informatics, University of Edinburgh invites applications for a Research Associate position in natural language processing and machine learning. The research project is in the area multimodal natural language understanding and generation. 

This post is full-time (35 hours per week), fixed term for 24 months, regular on-campus working. 

The postdoctoral researcher will be supervised by  Mirella Lapata and funded by  UKRI (the UK Research and Innovation National funding agency) and will join the Edinburgh NLP group (https://edinburghnlp.inf.ed.ac.uk/), one of the largest and most active NLP research groups in the world (see http://csrankings.org/#/index?nlp&world). There are many collaborative opportunities, both within the NLP group as well as across the School of Informatics (which includes faculty working on machine learning, computer vision, speech processing, and social computing). 

We are looking for a Postdoctoral Research Associate to work on genome stability in budding yeast Saccharomyces cerevisiae. Our laboratory is interested in telomere biology and DNA replication and repair mechanisms. This particular project will be focused on understanding how cells respond to telomerase insufficiency and other compromised genome signals. You will be using live cell imaging in combination with fluorescently tagged proteins to address the scientific questions at the single cell level.

You will be responsible for designing and conducting experiments, recording and analysing your own data and presenting them during lab meetings as well as summarising them for a publication. The responsibilities will also involve updating the databases of lab reagents, ordering materials and possibly helping to supervise undergraduate students. 

This position is affiliated with the UKRI APRIL AI Hub that aspires to develop AI tools to accelerate innovation across semiconductor technologies, novel microchip designs and system architectures – leading to faster, cheaper, greener and overall, more power-efficient electronics. As one of nine UKRI funded AI Hubs, this is a highly visible programme both nationally and internationally. 

The post-holder will work closely with a team of talented researchers and the APRIL operations team to lead the development of novel AI capabilities, tools and methodologies that can enhance the productivity of engineers in designing, developing and testing advanced electronic devices and systems. More specifically, the post-holder should have experience in developing and introducing AI tools in electronics testing and verification for predicting what to test and when. The research spans from improving scenario coverage in certification tests across devices/systems to automatically deciphering underlying physical mechanism is emerging beyond-CMOS devices.

The post-holder will have the ability to engage with world-leading experts across AI and electronics both at Edinburgh and in other UK higher education (HE) institutions but also industrial partners to ensure relevance of their Research in addressing state-of-art challenges in electronics. 

The successful candidate will have experience of project development and project leadership in a research context, together with excellent communication, presentation, and organisational skills. They will enjoy working in a dynamic environment and be able to work on their own initiative as well as being an active team member. The role will report to the APRIL Hub Director (Principal Investigator), with on-going engagement with other researchers in the Hub as well as academic leads. 

We are looking for a statistical geneticist with experience in large scale analyses of genomic data to work on a post funded by the National Institute for Health Research (NIHR) that aims are harness the use, integration and interpretation of large or high dimensional genetic and genomic datasets to investigate multi-morbidity. This post focuses on developing of mathematical models to analyse population-wide genetic and environmental factors linked to multimorbid clusters and to identify causal paths of disease progression and aggregation.

The successful candidate will lead a research programme to understand multi-morbidity in human populations. The successful candidate will interact with a large research community within the Artificial Intelligence community, genomics and health research (https://www.nihr.ac.uk/news/nihr-awards-12-million-to-artificial-intelligence-research-to-help-understand-multiple-long-term-conditions/28581, https://www.ed.ac.uk/usher/news-events/news-2021/artificial-intelligence-multimorbidity-nihr) 

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. 

A postdoctoral research position is available in the lab of Dr Susan Johnston (Institute of Ecology & Evolution) on evolutionary genomics of recombination rate variation in wild birds and mammals. We are looking for an enthusiastic and motivated postdoc to work with genomic data to characterise variation in population- and individual-level recombination landscapes wild long-term wild studies.

The project is part of a Royal Society-funded project on genetic basis and evolution of recombination variation. Meiotic recombination (i.e. chromosomal “crossovers”) is beneficial as it promotes proper chromosome segregation and creates new combinations of alleles upon which selection can act. However, it has the cost of increasing mutations and can break up previously beneficial allele combinations. Despite these trade-offs, relatively little is known about how and why the rate of recombination varies, particularly between the sexes (known as heterochiasmy) or between individuals, populations and species. Our group aims to better understand the causes and consequences of recombination rate variation in wild and domesticated populations.

This project will use genomic data in long-term pedigreed mammal and bird studies to investigate the causes, consequences, and correlates on variation in recombination landscapes, with a specific focus on sex differences. The PDRA will take advantage of an established analytical pipelines for estimating crossover positions within pedigrees and will investigate cross-sex variation in recombination landscapes. In addition, the PDRA will use whole-genome sequence data from unrelated individuals to investigate fine-scale recombination landscapes at the population level. The project includes funds for genotyping/sequencing, training, computing and attending international conferences. There is scope to tailor the project to the skills and interests of the PDRA, and to develop independent lines of research.

Applicants should have a strong background in genetics and a PhD in a relevant subject area (population and/or quantitative genetics, evolutionary biology, and/or working with recombination data). Experience working with genomic data and bioinformatics skills are essential, as is a strong track record of independent and creative thinking.

The School of Chemistry are looking to recruit a Postdoctoral Research Associate – chemical assembly and single-molecule detection of transmembrane processes (Cockroft/Horrocks groups)

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.

We are looking for an experienced and highly motivated Postdoctoral Research Fellow to join the Baillie Laboratory (www.baillielab.net), led by Prof Kenneth Baillie at the Roslin Institute and Baillie Gifford Pandemic Science Hub. 

The Baillie Lab is an interdisciplinary team of dedicated and highly capable people, focused on using genetics to find new therapies and treatments for critically ill patients. The team has made several contributions that have already improved medical practice. This includes using genetics to find the cause of unknown hepatitis in children (Nature, 2023a; Nature, 2023b) and identifying 49 genetic variants underlying with critical illness in COVID-19 (Nature, 2023; Nature, 2022). 

The Baillie Lab run several large-scale projects and studies including GenOMICC (www.genomicc.org), ISARIC4C (www.isaric4c.net) and the Outbreak Data Analysis Platform (www.odap.ac.uk) 

The aim of the role is to use genomic data to understand the mechanisms why patients respond differently to infection and to identify potential therapeutic targets to improve treatment outcomes for critically-ill patients. 

This post is advertised as full-time (35 hours per week); however, we are open to considering part-time or flexible working patterns. 

The positions are funded by Tadahiro Oh’s ERC Consolidator Grant “SingStocDispDyn”. The projects include a variety of possible research directions in nonlinear dispersive PDEs, stochastic PDEs, harmonic analysis and probability. The successful candidates are expected to contribute to undergraduate teaching and projects for further enhancing their career development. The appointees will join our thriving and growing Analysis Group within the School of Mathematics.

The School of Engineering seeks to appoint a Research Associate in Single-Photon LIDAR Technology. This Research Associate position will contribute to the project Compact, High-Resolution 3D Vision within the Institute for Integrated Micro and Nano Systems (IMNS) at the University of Edinburgh.

We are looking for a post-doctoral researcher to operate as post-doctoral research scientist in Tim Bean’s shellfish biology research group. The selected applicant will work as postdoc on the IGNITION project within a group conducting research into many aspects aquaculture species biology from the genetics of key production traits, through to disease diagnostics, host pathogen interactions, response to stress and the impact of nutrition. It is expected that the successful applicant will have excellent molecular biology and bioinformatics skills, including preparation and analysis of samples for RNAseq and single-cell or single-nuclei RNAseq. The applicant will have practical experience working with crustaceans and performing pathogen challenges in laboratory scenarios. The position requires a self-motivated and highly organized individual with excellent communication skills. The role will involve direct supervision of junior members of staff and students, and working directly on multiple research outputs at any one time in the group. The postdoc will have the opportunity to work directly with the PI in developing independent projects and lines of research.

We are looking for a motivated postdoctoral researcher to conduct basic research into sensorimotor plasticity in the visual cortex of mice, by utilizing virtual reality systems alongside in vivo whole cell recordings, plasticity paradigms, and optogenetics.

The School of Informatics at the University of Edinburgh is inviting applications for a Research Associate in Machine Learning and Artificial Intelligence with a particular focus on method development for Edge Devices, Scenarios and Environments. The successful candidate will be directly working with Amos Storkey (Principle Investigator) in the School of Informatics, and Elliot Crowley (co investigator) in the School of Engineering. The post will be based in Informatics.

The School of Informatics is one of the largest research centres in Computer Science in Europe, and it has been ranked #1 in the UK in terms of research power by a large margin. Informatics, Edinburgh is world renowned in Machine Learning and Reinforcement Learning, publishing in all the top venues in these fields. We are offering an exciting opportunity to work in an interdisciplinary, collaborative, friendly, and supportive environment, integrating different sub-fields of within Artificial Intelligence. 

Reinforcement learning (RL) algorithms aim to train a decision policy for an agent to achieve a specified task in an environment. The agent’s policy is trained by choosing actions which maximise the cumulative rewards received by the agent from its environment. With the introduction of deep learning into RL, “deep RL” algorithms have achieved unprecedented scalability, enabling the solution of complex decision tasks, such as autonomous driving [1] and beating human champions in games such as Go [2]. However, a current limitation of deep RL is that the training process typically requires orders of many millions of environment interactions in the precise environment (i.e. training data), which is infeasible in real-world applications where obtaining samples poses a significant bottleneck. Good transferability between different related environments is also still not generally achievable. Thus, developing approaches to improve the sample efficiency of deep RL algorithms, i.e. learning good policies with minimal data or from information learnt elsewhere, is a high-priority research topic.

We are looking for exceptionally talented and motivated computational scientist to take up a fully funded position as postdoctoral research associate (PDRA) in deep learning for drug discovery, as part of the EPSRC Early Career Fellowship ‘GREET: Generative Recombinant Enzyme Engineering for Therapeutics’, led by Dr Giovanni Stracquadanio. 

We are an interdisciplinary group based at the School of Biological Sciences at the University of Edinburgh, interested in addressing challenges in healthcare and biotechnology, and aiming at continuously improving our strong publications and funding track record (www.stracquadaniolab.org).

This is an exciting opportunity for a Senior Research Fellow in Medical Statistics to join Edinburgh Clinical Trials Unit (ECTU), a leading registered trials unit based within the Usher Institute, University of Edinburgh. ECTU has a proven track record on delivering research and answering important questions about treatment and service delivery within the NHS. We work closely with patient groups and clinicians who are outstanding in their field.

As a key member of the statistics leadership team within ECTU and highly valued academic contributor, the post holder will have a high level of involvement in the statistical design, analysis and reporting of clinical research projects. The post holder will also be expected to be involved as a co-applicant on funding applications with the aim of generating substantial research income and growth for the ECTU portfolio through collaborative involvement. In addition, the post holder will be encouraged to lead on trials methodological research projects, and develop statistical methodological expertise within the Unit.

Applicants must have an MSc or PhD in medical statistics and a significant level of experience relating to the design, conduct, analysis, interpretation and reporting of clinical trials.  Extensive experience of writing funding applications is also essential to the post. We are looking for an enthusiastic, resourceful and highly organised person who is able to work independently, managing their own workload and working as part of a multidisciplinary team. Applicants will possess experience of managing staff and projects and will have good problem-solving and interpersonal skills.

This post is full-time (35 hours per week), and is available immediately for 24 months in the first instance.  Part-time work would also be considered.  Informal enquiries may be directed to Prof Steff Lewis Steff.Lewis@ed.ac.uk or Prof. Chris Weir Christopher.Weir@ed.ac.uk. If you are interested but don’t have exactly the right skills and experience, or are over-qualified for this particular role, please do get in touch to talk about opportunities.

This position is affiliated with the UKRI APRIL AI Hub that aspires to develop AI tools to accelerate innovation across semiconductor technologies, novel microchip designs and system architectures – leading to faster, cheaper, greener and overall, more power-efficient electronics. As one of nine UKRI funded AI Hubs, this is a highly visible programme both nationally and internationally. 

The post-holder will work closely with a team of talented researchers and the APRIL operations team to support the development of novel AI capabilities, tools and methodologies that can enhance the productivity of engineers in designing, developing and testing advanced electronic devices and systems. More specifically, the post-holder will be able to build “digital twins” for modelling device/systems performance, with input from automated testing routines. The research spans from automated process for new and emerging semiconductor devices to efficient modelling of complex electronic circuits and architectures. 

The post-holder will have the ability to engage with world-leading experts across AI and electronics both at Edinburgh and in other UK higher education (HE) institutions but also industrial partners to ensure relevance of their Research in addressing state-of-art challenges in electronics. 

This position is affiliated with the UKRI APRIL AI Hub that aspires to develop AI tools to accelerate innovation across semiconductor technologies, novel microchip designs and system architectures – leading to faster, cheaper, greener and overall, more power-efficient electronics. As one of nine UKRI funded AI Hubs, this is a highly visible programme both nationally and internationally. 

The post-holder will work closely with a team of talented researchers and the APRIL operations team to support the development of novel AI capabilities, tools and methodologies that can enhance the productivity of engineers in designing, developing and testing advanced electronic devices and systems. More specifically, the post-holder will be able to develop and introduce AI tools into commercially available  circuit design tools that can autonomously synthetise circuits and systems architectures. The aim is to drastically reduce the design time and optimise the transfer of known topologies into new CMOS technologies. 

The post-holder will have the ability to engage with world-leading experts across AI and electronics both at Edinburgh and in other UK higher education (HE) institutions but also industrial partners to ensure relevance of their Research in addressing state-of-art challenges in electronics. 

The School of Informatics, University of Edinburgh invites applications for a Post-Doctoral Research Associate in Natural Language Processing and Machine Learning to work with Dr Pasquale Minervini in the Edinburgh NLP Group. The project is funded by Huawei via the Huawei-Edinburgh Joint Lab initiative.

The researcher will work on projects involving the design and application of improving the robustness and trustworthiness of Large Language Models when solving complex reasoning tasks, while improving their explainability and generalisation properties. They will be part of the Edinburgh NLP Group, a world-leading research group in Natural Language Processing.

The School of Informatics is one of the largest research centres in Computer Science in Europe and is ranked #1 in the UK in terms of research power by a large margin. The Edinburgh NLP Group is consistently ranked among the world’s leading research groups in Natural Language Processing. We offer an exciting opportunity to work in an interdisciplinary, collaborative, friendly, and supportive environment that integrates various fields of Computer Science and Artificial Intelligence.

Large Language Models (LLMs) have significantly advanced NLP by providing more accurate solutions for a wide variety of problems, ranging from (open domain) question answering to complex reasoning tasks. Still, LLMs tend to produce hallucinations — sentences that appear fluent but are semantically nonsensical, often containing factual inaccuracies — with potentially catastrophic implications. This project aims to explore, develop and benchmark strategies for improving the factuality and reliability of LLMs when answering complex questions and solving complex tasks – for example, via Chain-of-Thought reasoning.

We are looking for an enthusiastic, organised and motivated post-doctoral scientist with experience in image processing and analysis that could support our expanding PET research programme. 

You will have the opportunity to join the “PET is Wonderful” team working at the University of Edinburgh to develop new PET imaging biomarkers. We have a vibrant and rapidly expanding programme of PET research with over 25 different radiotracers in our current portfolio. You will have the opportunity to work on academic and industry-sponsored projects across the medical research pipeline from organic chemistry (bench) to clinical imaging (bedside). The University of Edinburgh houses three preclinical PET systems and three clinical PET systems coupled with CT or MRI. Our radiochemistry facility has also recently been upgraded and expanded to house eleven hot cells (3 dedicated to R&D use and 8 for GMP productions) and a cyclotron. Further details on the job being offered can be found below.   

The University of Edinburgh is part of the CO2RE GGR Hub which includes co-investigators at the Universities of Bristol, Leeds, London (Imperial College and University College) and Manchester, led by the Smith School of Enterprise and the Environment at Oxford.

Reaching our national and global climate goals will require not only the reduction of emissions of greenhouse gases, but also the scaling up of a range of techniques, so called GGRs, that take greenhouse gases back out of the atmosphere permanently. To meet this need, UKRI has launched a £31.5m GGR-D programme, which includes CO2RE and five demonstration projects around the UK. CO2RE will conduct cross-cutting research on the environmental, economic, social, cultural, ethical, legal and governance issues around GGR.

The successful candidate will be based in the Faculty of Law at the University of Edinburgh and part of a wider team of academic researchers who are working on the governance, legal and ethical factors, as part of the overall project.

We are looking for a postdoctoral researcher with a background in climate and/or regulatory law who will bring a mix of socio-legal and empirical research expertise to the project. Key responsibilities in the role include providing leadership and expertise in legal analysis, running empirical research studies and conducting data analysis, planning knowledge exchange activities with partners and the public, contributing to the project toolkit development, disseminating high quality research outputs and being a core member of the interdisciplinary team.

The post-holder line manager is Mr Navraj Singh Ghaleigh, and will be based in the School of Law, University of Edinburgh. The post-holder will work closely with other investigators at the University of Edinburgh, and across the CO2RE GGR Hub and GGR-D programme.