Computational Researcher Edinburgh - Bio-Quarter (Royal Infirmary), Midlothian, United Kingdom [...]

We are looking for a highly motivated computational researcher with a proven record in machine learning and computer vision/bioimage analysis to take the computational lead on a pioneering project to map the diversity of connections in the brain.
The opportunity:
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. This position is fixed term until 31 Oct 2025 in the first instance, with the possibility of extension.
Understanding the complexity of the brain in health and disease remains a landmark challenge. The aim of our project is to quantitatively map the trillions of nerve cell connections (synapses) across the brain. This highly ambitious goal will be delivered by a team of dedicated scientists using cutting-edge AI-based image analysis methods to decode terabyte-level data obtained by brain microscopy. You will play a key role by working closely with our team of experimental and computational neuroscientists to develop and maintain the image data analysis pipeline that detects and characterises these synaptic connections. This post offers a unique opportunity to leverage state-of-the-art AI technologies to address basic science questions, including how this architecture of brain connections is impacted by pathology. While we value experience, we equally welcome applications from suitably qualified candidates who may be earlier in their career but can demonstrate a willingness and capacity to develop and expand their skills as they grow into the role.
As part of this application you should include a one page document outlining how you meet the essential criteria for this post noted on the job description.
Your skills and attributes for success:
Degree in computer science or related computing/bioinformatics discipline.
Experience in machine learning and image analysis.
Experience in GPU-based programming or in a distributed-computing environment would be advantageous for this post.
An interest in neuroscience and brain anatomy.
An outstanding team player who will thrive within a multidisciplinary, highly collaborative research group .
Click to view a copy of the full job description(opens new browser tab).
As a valued member of our team you can expect:
A competitive salary of £37,099 - £44,263.
An exciting, positive, creative, challenging and rewarding place to work.
To be part of a diverse and vibrant international community
Comprehensive Staff Benefits, such as a generous holiday entitlement, a defined benefits pension scheme, 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 total value of your pay and benefits
Championing equality, diversity and inclusion
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)
Key dates to noteUnless 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. The University is able to sponsor the employment of international workers in this role.
If successful, an international applicant requiring sponsorship to work in the UK will need to satisfy the UK Home Office’s English Language requirements and apply for and secure a Skilled Worker Visa.
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
The Centre for Clinical Brain Sciences (CCBS; Director Professor Siddharthan Chandran) is part of Edinburgh Neuroscience and Edinburgh Medical School. CCBS comprises the Divisions of Clinical Neurosciences (Head: Professor Siddharthan Chandran), Psychiatry (Head: Professor Daniel Smith) and Neuroimaging Sciences (Head: Professor Joanna Wardlaw). Our work integrates laboratory science, data science, health informatics and clinical research to study the causes, consequences and treatment of all major neurological and psychiatric disorders. Methodological strengths include neuroimaging, clinical trials, neuropathology, neuropsychiatric genetics and regenerative neurology.
We have 56 Principal Investigators, 70% of whom are NHS clinicians, grounding our work in clinical need and facilitating translation into patient benefit. We produce more than 500 research outputs per year, leading to improved patient care and NHS policy changes, with substantial impact on morbidity and mortality. CCBS researchers attracted £49M in external funding over the last three years and we collaborate globally, leading national and international consortia in neurodegenerative disorders, global mental health, psychiatric conditions, stroke and small vessel disease.
With bases at Edinburgh BioQuarter, Royal Edinburgh Hospital and Western General Hospital, CCBS locations link laboratory and clinical science with informatics, public engagement and commerce to facilitate creative interdisciplinary working. CCBS hosts c.60 postgraduate students, mostly PhDs. We are particularly strong in clinical PhD training, with bespoke funding schemes (e.g. Rowling Scholars), and we host the Wellcome Translational Neuroscience Doctoral Training Programme. Through generous philanthropic support, CCBS has established many specialist research hubs that are expanded by community fundraising and which engage closely with patient groups, policy-makers and public.
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