Postdoctoral Fellowship (17) at University of Edinburgh, Scotland, United Kingdom

The University of Edinburgh is a world-class organisation. We look for the best in the field across all disciplines and provide a working environment where academics can develop their careers and passion for their chosen subject area. We offer the full range of academic roles and have a genuine focus on our student’s performance and wellbeing. 

Improving diagnosis for rare genetic diseases requires innovative, scalable, and explainable machine learning (ML) systems to interpret complex genomic and clinical data. As part of the Welcome Trust funded PARADIGM project, an initiative aiming to transform genomic medicine by identifying new causes of monogenic disease and developing annotated resources for the scientific community. This role will focus on advancing ML pipelines, frameworks, and tools to enhance variant interpretation, gene-disease models, and clinical decision support. 

The successful candidate will collaborate with academics, software engineers, curators, clinical scientists, clinicians, and patient groups to design FAIR (Findable, Accessible, Interoperable, Reusable) and resource-efficient ML solutions for real-world deployment. Key responsibilities include developing standards-compliant, reusable modelling frameworks for rare genetic disease knowledge representation from multi-modal data, creating scalable and privacy-preserving computing solutions for genetic and health data, and integrating novel ML technologies into the broader PARADIGM project workflow. The role also involves proactively disseminating work through national and international collaborations, ensuring explainable AI/ML for clinical use, and supporting students through mentorship and knowledge-sharing activities. 

This position offers the opportunity to contribute to cutting-edge research, work in the Biomedical Informatics Group, a multidisciplinary team in the School of Informatics, and shape the future of genomic medicine. 

The University of Edinburgh is a world-class organisation. We look for the best in the field across all disciplines and provide a working environment where academics can develop their careers and passion for their chosen subject area. We offer the full range of academic roles and have a genuine focus on our student’s performance and wellbeing. 

Improving diagnosis for rare genetic diseases is a critical challenge, requiring innovative approaches to extract and interpret complex biological and clinical information. As part of the Welcome Trust funded PARADIGM project, an initiative aiming to transform genomic medicine by identifying new causes of monogenic disease and developing annotated resources for the scientific community. This role will focus on advancing biomedical natural language processing (NLP) to enhance variant-phenotype mapping, gene-disease models, and clinical decision support. 

The successful candidate will collaborate with academics, curators, clinical scientists, clinicians, and patient groups to identify practical applications of NLP in real-world scenarios. Key responsibilities include developing novel NLP approaches to extract phenotypic information from unstructured data (e.g., literature, EHRs, clinical notes), creating domain-specific text summarisation tools, and integrating these technologies into PARADIGM’s broader research goals. The role also involves proactively disseminating work through national and international collaborations, ensuring explainable AI/ML for clinical use, and supporting students through mentorship and knowledge-sharing activities.

This position offers the opportunity to contribute to cutting-edge research, work in the Biomedical Informatics Group, a multidisciplinary team in the School of Informatics, and shape the future of genomic medicine. 

The University isn’t just any employer. We are part of a local community and a contributor to global thinking, progress and research. In Edinburgh, you are in one of the world’s most attractive cities with active arts and social sectors, while working in a University that has made significant contributions to society, medicine, physics and teaching for over four centuries. Our people have helped create the modern world and are working on more ground-breaking technologies and practices. Join the University of Edinburgh and you’ll be making a difference to everything around you.

The University of Edinburgh is a world-class organisation. We look for the best in the field across all disciplines and provide a working environment where academics can develop their careers and passion for their chosen subject area. We offer the full range of academic roles and have a genuine focus on our students performance and wellbeing.

The University of Edinburgh is seeking a Grade 7 Research Associate (Academic) to contribute to an international programme developing and evaluating virtual physics laboratories to widen access to high-quality practical STEM learning in Northern Ghana. The role will work within a multidisciplinary team and with project partners in Ghana and internationally, addressing constraints such as limited laboratory infrastructure, intermittent internet connectivity, and device/power limitations.

You will take a defined lead role in the design, implementation, validation, and deployment of interactive, browser-based virtual laboratory experiences and associated learning activities. Core technologies are expected to include JavaScript/TypeScript, Vue.js, Three.js, WebGL, WebAssembly, and physics engines such as Rapier. You will contribute to robust software development practices (version control, testing, release management, and documentation), ensuring that simulations are scientifically rigorous, transparent about limitations, and usable on low-cost devices.

A key aspect of the post is supporting offline/low-connectivity delivery, for example packaging and deploying resources to standalone local hosting platforms, and adapting learning analytics or formative feedback approaches to work reliably in constrained environments. You will also contribute to participatory co-design with teachers and universities in Ghana, and to capacity building through training materials, templates, and practical documentation to support partner sustainability.

The post-holder will contribute to educational evaluation and evidence generation using methods already, or to be, developed in our wider remote laboratories research group. These include surveys and and the analysis of click data (e.g. using Python) and producing outputs suitable for reports, stakeholders, and academic dissemination (papers, conference presentations, workshops, and open resources as appropriate).

We are looking for a candidate with a PhD completed or near completion (or equivalent experience) in a relevant area, strong technical problem-solving ability, and demonstrated experience building interactive web-based applications or in developing science/engineering simulations. Excellent communication skills and the ability to work effectively across cultures and disciplines are essential.

The successful applicant will have a PhD in the field of equine cardiology, with significant experience using in vivo electrophysiology, electroanatomic mapping systems, and advanced echocardiography.  Excellent communication skills, competency in statistical analysis and presentation of data are also prerequisites. 

The research goal involves delivering data from advanced imaging to use in computational modelling of the Thoroughbred heart.  You will be working within one of the world’s leading universities and will have opportunities for professional development as well as acquiring subject matter expertise. There will be opportunities to develop new skills and broaden your experience in this leading-edge research team. Some opportunities for clinical cardiology will also be available, when this aligns with the aims of the research project.  The successful applicant will also be expected to contribute to the supervision of undergraduate and postgraduate student projects in the equine unit, in the field of equine cardiology research.  

This post is full-time (35 hours per week); however, we are open to considering 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 seeking a highly motivated postdoctoral researcher to join Professor Andy Baker’s laboratory in the Institute for Neuroscience and Cardiovascular Research at the University of Edinburgh. This position is funded by a European Research Council (ERC) grant and will focus on developing and characterising advanced therapeutic approaches for cardiovascular disease, including gene- and RNA-based interventions.

You will work within a multidisciplinary team of basic and clinician scientists, contributing to experimental design, data generation and analysis, and publication of high-impact research. The role offers excellent opportunities for scientific development, collaboration, and career progression in an internationally recognised cardiovascular research environment.

With roles from hospitality to research, there’s a career for everyone at the University of Edinburgh. We can offer opportunities for you to develop in your career and make a real difference in the communities around us while contributing to the world at large. 

We offer careers and roles in just about every area you can think of. Whether you are looking for entry-level, mid-career or roles at the top of your chosen specialism, we can offer you a career where you can flourish and make a real difference in the communities around us while contributing to the world at large. Our people come from a wide range of backgrounds, each bringing their abilities and experiences to our organisation. ​

The University isn’t just any employer. We are part of a local community and a contributor to global thinking, progress and research. In Edinburgh, you are in one of the world’s most attractive cities with active arts and social sectors, while working in a University that has made significant contributions to society, medicine, physics and teaching for over four centuries. Our people have helped create the modern world and are working on more ground-breaking technologies and practices.

Join the University of Edinburgh and you’ll be making a difference to everything around you. Be part of something bigger — where you’ll do meaningful work, grow and progress, be rewarded and recognised, and benefit from our strong commitment to your wellbeing. There are so many reasons to join us. 

The University of Edinburgh is a world-class organisation. We look for the best in the field across all disciplines and provide a working environment where academics can develop their careers and passion for their chosen subject area. We offer the full range of academic roles and have a genuine focus on our students performance and wellbeing.

The successful candidate will work alongside Dr Anne Templeton and other team members as part of an UKRI funded project ‘Simulating the impact of first responder communication strategies on citizen adherence in emergencies”.

The PDRA will be integral to key aspects of the project including monitoring the progression of the project, co-designing and preparing the studies, data analysis, and disseminating the findings to stakeholders.

An exciting opportunity is available to join the research group of Dr Chris Sibley as a post-doctoral research associate, and to dissect molecular mechanisms underlying the initiation and progression of motor neuron disease. Specifically, the candidate will work as part of a focussed team to determine the relevance of multiple identified targets of the TDP-43 protein in the early stages of disease biology and then develop corrective approaches to rescue appropriate disease biology in clinically relevant human stem cell models. This exciting research project will combine work with human induced pluripotent stem cell models, molecular biology methods (e.g. cloning, qPCR), functional genomics and bioinformatics workflows. The staff member will benefit from joining the vibrant networks of Edinburgh Neuroscience and the Euan MacDonald Centre.  

The University of Edinburgh is a world-class organisation. We look for the best in the field across all disciplines and provide a working environment where academics can develop their careers and passion for their chosen subject area. We offer the full range of academic roles and have a genuine focus on our student’s performance and wellbeing.  

We value colleagues with drive, determination and a passion for what they do. We are a place where everyone is welcome and offer a range of policies and benefits designed to support you in building the right meaningful flexibility that works for you. 

The University of Edinburgh is a world-class organisation. We look for the best in the field across all disciplines and provide a working environment where academics can develop their careers and passion for their chosen subject area. We offer the full range of academic roles and have a genuine focus on our students performance and wellbeing.

The School of Informatics, University of Edinburgh invites applications for a Postgraduate research associate.

Candidates must have or be near completion of a PhD degree in Computer Science or related field and a strong research track record demonstrated through publications at top-tier venues. We are looking for a highly motivated candidate with strong initiative and commitment to excellence, and an ability to conduct world-class research in a team setting.

The University of Edinburgh is a world-class organisation. We look for the best in the field across all disciplines and provide a working environment where academics can develop their careers and passion for their chosen subject area. We offer the full range of academic roles and have a genuine focus on our students performance and wellbeing.

This post presents an exciting opportunity to join a research laboratory focussed on optimising fertility preservation options for young women and girls undergoing cancer treatment. The Centre for Reproductive Health at the University of Edinburgh has a strong track-record in deliverying translational research, with great success in bench to bedside approaches that are recognised worldwide.

People have always been at the heart of our work. As part of the University, you are a part of our community. We are looking for people with drive, determination, and a passion for what they do. We are a place where everyone is welcome and offer a range of policies and benefits designed to support you in building the right meaningful/personalised flexibility for you.

We are looking for a highly skilled and motivated postdoctoral researcher to work on extracellular RNA and it role in immune regulation. Specifically we build on our studies of exRNAs released from parasites (1,2) to examine more broadly the features of exRNA released by eukarya and bacteria that regulate immune signalling in mammalian cells (3). The award holder will be part of a multi-disciplinary, international team funded by the Human Frontiers in Science Program and will join Amy Buck’s lab in the Institute of Immunology & Infection Research, University of Edinburgh.  Applicants must have a PhD and significant research experience since there undergraduate degree. The post requires advanced knowledge of RNA biology, biochemistry, microbiology and immunology.  An overview of the laboratory can be found here: www.bucklab.org and questions should be directed to [email protected]

We are seeking a highly skilled and motivated Postdoctoral Researcher to join our Translational Cerebral Amyloid Angiopathy (CAA) Research Lab at the BHF-UK DRI Centre for Vascular Dementia Research. This role is ideal for someone with a strong technical and computational and background who is passionate about applying advanced data analysis to complex biological systems.

As a Postdoctoral Researcher, you will be performing in vivo optical microscopy experiments in rodent models. You will play a central role in developing and implementing computational approaches for the acquisition and analysis of high-resolution optical imaging data. Working with state-of-the-art in vivo two-photon microscopy datasets, you will design analysis pipelines, develop code, and extract meaningful insights from large, multidimensional imaging datasets. Your work will directly contribute to understanding the mechanisms underlying CAA and vascular dysfunction in neurodegenerative disease.

Alongside your computational focus, you will contribute to experimental workflows, including in vivo imaging studies and ex vivo tissue analysis, ensuring strong integration between data acquisition and analysis. This is a collaborative and interdisciplinary environment, where you will work closely with experimental researchers while leading on computational strategy and innovation. 

We are looking for someone with strong programming skills (e.g. Python, MATLAB), experience in image processing and analysis, and the ability to handle complex datasets with precision and creativity. A proactive mindset, attention to detail, and enthusiasm for developing new computational methods are essential.

We are committed to supporting your development. As part of the BHF-UK DRI Centre for Vascular Dementia Research, you will be embedded in a world-class research environment with access to cutting-edge technologies and opportunities to expand your computational and scientific expertise.

These roles are an excellent opportunity to actively participate in and shape QSL’s projects, consolidating its position of international leadership in the field. The successful applicant will work inside the largest quantum software academic team in the UK based in one of the most renowned computer science departments in the world. QSL is a dynamic and interdisciplinary environment composed of a diverse cohort of colleagues passionate about bringing quantum computation to reality. This will be a unique experience of professional growth, working on the timely and exciting goal building the foundations of critical part of the quantum computation stack directly under the UK Missions 1 umbrella. Ideal candidates combine research excellence with a results-oriented approach. 

We welcome both local (UK-resident) and international applicants from all backgrounds and particularly encourage applications from female researchers, minority ethnic groups, first-generation academics and STEM researchers, and other underrepresented groups in academia. We are also very open to applications from those with non-traditional career paths, including individuals with family, caring, or health-related career breaks, or those who have moved into academia from a career in another sector. We are strongly committed to offering everyone an inclusive and non-discriminatory working environment. 

The posts will be for 2 + 1 years: an initial 2-year appointment, with eligibility for a 1-year extension subject to a successful review by the project PI
This post is full-time. We are open to considering requests for hybrid working, on a non-contractual basis, combining remote and regular on-campus working.

For full details of the essential and desirable skills and attributes required for the position, please refer to the full job description here

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. 

 The successful candidate will have excellent communication, organisation, and technical 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. 

The research group of Dr. Nina Kudryashova, a Royal Society University Research Fellow, at the Institute for Machine Learning (IML) at the University of Edinburgh, invites applications for a Postdoc / Research Associate (36 months), to contribute to cutting-edge research in computational neuroscience, developing algorithmic foundations for closed-loop experimentation.

The post holder will be supervised by the principal investigator Dr. Nina Kudryashova. The group has established links to experimental neuroscience groups in Edinburgh (Duguid, Rochefort, Karnani) and Newcastle Hospitals NHS Foundation Trust (Bashford). The post holder will also have the opportunity to collaborate with colleagues in a wide range of specialties across the School, including in computational neuroscience (e.g. Hennig, Onken, Chadwick), computational cognitive neuroscience (e.g. Series, Peters), machine learning (e.g. Mac Aodha, Bilen, Sevilla-Lara, Vergari, Malkin, Borovitskiy), probabilistic programming (e.g. Narayanaswamy, Kammar, Belle), as well as in robotics and neurotechnology (e.g. Nazarpour, Webb).

The central purpose of the job is to investigate data-driven machine learning methods to enable the identification and control of neural population dynamics, providing actionable predictions for designing next-generation systems neuroscience experiments. 

Your project will build on the group’s work on disentangling neural code for feedforward and feedback-driven control of movement [Kudryashova 2025, bioRxiv]. Our primary research aim is getting insights into closed-loop brain-environment interaction, particularly learning from behavioral perturbations or targeted neural stimulation. However, other research directions within NeuroAI will also be available for the post holder to explore. Being part of a newly established group, this post offers a unique chance to influence the trajectory of our group’s work and contribute significantly to emerging NeuroAI research directions.