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The University of Edinburgh
Research Associate
City of Edinburgh Hybrid 2-5 yrs exp£41k – £49k / year
Machine LearningBioinformaticsComputational BiologyPythonHigh-Performance Computing
Requirements
Candidates must have a PhD or be near completion in a relevant field, with expertise in machine learning and experience in genomics or biomedical data analysis. Strong programming skills in Python and experience with high-performance computing environments are essential.
Job Description
Job Description
UE07: £41,064.00 - £48,822.00 Per Annum.
College of Science and Engineering / School of Informatics / Institute for Machine Learning
Full Time - 35 Hours per week.
Fixed Term Contract, if applicable: 01/07/2026 – 31/03/2028 - 21 months.
We are looking for a Post Doctoral Researcher Associate in Biomedical Machine Learning Systems.
The Opportunity
Together we can do great things. Be part of something bigger.
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.
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.
Your Skills And Attributes For Success
Essential Skills & Experience:
This post is Full Time (35 hours per week); we are open to considering requests for hybrid working (on a non-contractual basis) that combines a mix or remote and regular on-campus working.
Click to view a copy of the full job description (opens new browser tab)
How To Apply
Please include the following documents in your application:
The University of Edinburgh holds a Silver Athena SWAN award in recognition of our commitment to advance gender equality in higher education. We are members of the Race Equality Charter, and we are also Stonewall Scotland Diversity Champions, actively promoting LGBT equality.
Prior to any employment commencing with the University, you will be required to evidence your right to work in the UK. Further information is available on our right to work webpages (opens new browser tab).
The University may be able to sponsor the employment of international workers in this role. This will depend on a number of factors specific to the successful applicant.
Key Dates To Note
The closing date for applications is 19 June 2026.
Interviews will be held after the clsoing date.
If invited for interview you will be required to evidence your right to work in the UK. Further information is available on our right to work webpages (opens new browser tab).
Unless stated otherwise the closing time for applications is 11:59pm GMT. If you are applying outside the UK, the closing time on our adverts automatically adjusts to your browsers local time zone.
About Us
As a world-leading research-intensive University, we are here to address tomorrow’s greatest challenges. Between now and 2030 we will do that with a values-led approach to teaching, research and innovation, and through the strength of our relationships, both locally and globally.
About The Team
Informatics is the study of how natural and artificial systems store, process and communicate information. Research in Informatics promises to take information technology to a new level, and to place information at the heart of 21st century science, technology and society. The School enjoys collaborations across many disciplines in the University, spanning all three College, and also participates as a strategic partner in the Alan Turing Institute and is home to a number of Centres for Doctoral Training.
The School provides a fertile environment for a wide range of studies focused on understanding computation in both artificial and natural systems. It attracts students around the world to study in our undergraduate and postgraduate programmes. Informatics is one of seven schools in the College of Science and Engineering, at the University of Edinburgh. It is recognised for the employability of its graduates, its contributions to entrepreneurship, and the excellence of its research. Since the first Research Assessment Exercise in 1986, Informatics at Edinburgh has consistently been assessed to have more internationally excellent and world-class research than any other submission in Computer Science and Informatics. The latest REF 2021 results have again confirmed that ours is the largest concentration of internationally excellent research in the UK. This contributes to our ranking of consistently being in the top 30 world-wide.
We aim to ensure that our culture and systems support flexible and family-friendly working and recognise and value diversity across all our staff and students. The School has an active programme offering support and professional development for all staff; providing mentoring, training, and networking opportunities.
UE07: £41,064.00 - £48,822.00 Per Annum.
College of Science and Engineering / School of Informatics / Institute for Machine Learning
Full Time - 35 Hours per week.
Fixed Term Contract, if applicable: 01/07/2026 – 31/03/2028 - 21 months.
We are looking for a Post Doctoral Researcher Associate in Biomedical Machine Learning Systems.
The Opportunity
Together we can do great things. Be part of something bigger.
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.
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.
Your Skills And Attributes For Success
Essential Skills & Experience:
- PhD (or near completion) in a relevant field (e.g., Machine Learning, Bioinformatics, Computational Biology, or related disciplines).
- Demonstrated expertise in machine learning, particularly in genomics, rare disease research, or biomedical data analysis.
- Strong ML programming skills in Python and/or other relevant languages, with experience in optimising and deploying distributed compute tasks.
- Experience working with high-performance computing environments, including containerised systems (e.g., Docker, Kubernetes) for scalable and reproducible computational workflows.
- Ability to work collaboratively within interdisciplinary teams (academics, clinicians, curators, software engineers) and communicate complex technical concepts clearly.
- Experience with scientific writing, including the ability to publish in peer-reviewed journals and present research findings at conferences.
- Experience with API development and integration, including RESTful APIs or other standards for data exchange and interoperability.
- Familiarity with Model Configuration Protocols (MCP) for defining and deploying machine learning models in reproducible, scalable workflows.
- Experience with database systems (e.g., SQL/NoSQL) and knowledge graph construction (e.g., Neo4j, RDF triples) for organising and querying complex biomedical data.
- Familiarity with tools for data integration, transformation, or workflow orchestration in large-scale projects.
- Familiarity with ontologies (e.g., HPO, OMIM) and semantic technologies for knowledge graph construction.
- Experience with the use of GNNs in a multi-modal data integration setting (for example using fusion, hierarchical modelling, contrastive learning).
- Experience with variant-phenotype mapping, gene-disease model creation, or computational phenomics.
- Experience with explainable AI/ML and open-source software development.
- Experience mentoring students (undergraduate, MSc, or PGR) or contributing to educational initiatives.
This post is Full Time (35 hours per week); we are open to considering requests for hybrid working (on a non-contractual basis) that combines a mix or remote and regular on-campus working.
Click to view a copy of the full job description (opens new browser tab)
How To Apply
Please include the following documents in your application:
- CV
- Cover letter
- A competitive salary.
- An exciting, positive, creative, challenging and rewarding place to work.
- To be part of a diverse and vibrant international community.
- Comprehensive Staff Benefits, including generous annual leave entitlement, a defined benefits pension scheme, a wide range of staff discounts, family-friendly initiatives, and flexible work options. Check out the full list on our staff benefits page (opens in a new tab) and use our reward calculator to discover the value of your pay and benefits.
The University of Edinburgh holds a Silver Athena SWAN award in recognition of our commitment to advance gender equality in higher education. We are members of the Race Equality Charter, and we are also Stonewall Scotland Diversity Champions, actively promoting LGBT equality.
Prior to any employment commencing with the University, you will be required to evidence your right to work in the UK. Further information is available on our right to work webpages (opens new browser tab).
The University may be able to sponsor the employment of international workers in this role. This will depend on a number of factors specific to the successful applicant.
Key Dates To Note
The closing date for applications is 19 June 2026.
Interviews will be held after the clsoing date.
If invited for interview you will be required to evidence your right to work in the UK. Further information is available on our right to work webpages (opens new browser tab).
Unless stated otherwise the closing time for applications is 11:59pm GMT. If you are applying outside the UK, the closing time on our adverts automatically adjusts to your browsers local time zone.
About Us
As a world-leading research-intensive University, we are here to address tomorrow’s greatest challenges. Between now and 2030 we will do that with a values-led approach to teaching, research and innovation, and through the strength of our relationships, both locally and globally.
About The Team
Informatics is the study of how natural and artificial systems store, process and communicate information. Research in Informatics promises to take information technology to a new level, and to place information at the heart of 21st century science, technology and society. The School enjoys collaborations across many disciplines in the University, spanning all three College, and also participates as a strategic partner in the Alan Turing Institute and is home to a number of Centres for Doctoral Training.
The School provides a fertile environment for a wide range of studies focused on understanding computation in both artificial and natural systems. It attracts students around the world to study in our undergraduate and postgraduate programmes. Informatics is one of seven schools in the College of Science and Engineering, at the University of Edinburgh. It is recognised for the employability of its graduates, its contributions to entrepreneurship, and the excellence of its research. Since the first Research Assessment Exercise in 1986, Informatics at Edinburgh has consistently been assessed to have more internationally excellent and world-class research than any other submission in Computer Science and Informatics. The latest REF 2021 results have again confirmed that ours is the largest concentration of internationally excellent research in the UK. This contributes to our ranking of consistently being in the top 30 world-wide.
We aim to ensure that our culture and systems support flexible and family-friendly working and recognise and value diversity across all our staff and students. The School has an active programme offering support and professional development for all staff; providing mentoring, training, and networking opportunities.
Education
Postgraduate Degree
Skills
Machine LearningBioinformaticsComputational BiologyPythonHigh-Performance ComputingDockerKubernetesAPI DevelopmentDatabase SystemsKnowledge Graph ConstructionData IntegrationExplainable AIMentoringScientific WritingCollaborationCommunication