Research Fellow: Machine Learning for Multi-scale, X-ray Mapping of the Human Brain
2 weeks ago
Ref Number
B
Professional Expertise
Research and Research Support
Department
UCL BEAMS (B04)
Location
London
Working Pattern
Full time
Salary
£43,981-£52,586
Contract Type
Fixed-term
Working Type
On site
Available for Secondment
No
Closing Date
04-Jan-2026
About usUniversity College London (UCL) UCL is a multi-disciplinary university with a population of over 13,000 staff and 42,000 students from 150 different countries. Degree programmes are provided in Arts and Humanities, Built Environment, Brain Sciences, Engineering Sciences, Education, Laws, Life Sciences, Mathematical & Physical Sciences, Medical Sciences, Population Health Sciences and Social and Historical Sciences. For more information, please visit UCL Mechanical Engineering UCL Mechanical Engineering has been pioneering the development of engineering education, having taught the core discipline for over 165 years. UCL was home to the UK's first ever Professor of the Mechanical Principles of Engineering, Eaton Hodgkinson, in 1847. It was also where Sir Alexander Blackie William Kennedy introduced organized laboratory practicals in university education training; a world-leading educational innovation at the time.
About the roleWould you like to help build the first multiscale map of the human brain? We are seeking a Research Fellow to join UCL's MXI Lab and the Human Organ Atlas programme, using cutting-edge imaging and AI to transform neuroscience. You will develop deep-learning tools to analyse 3D brain scans from whole-organ to cellular scale, combining HiP-CT and MRI to reveal structural changes linked to diseases like ALS and Parkinson's. You'll coordinate imaging experiments, support data acquisition at the ESRF, and work with global collaborators to create open-access datasets that will shape the future of brain research. The post is funded for 2 years in the first instance, with the possibility of renewal. A job description and person specification can be accessed at the bottom of this page. For informal enquiries, please contact Dr Claire Walsh ( ) or Prof Peter Lee ). For application process queries, contact Ruikang Xue ).
About youYou will have a PhD in a relevant discipline (e.g., computational biology, engineering, biophysics, computer science) and experience in 3D imaging of brain tissue, image segmentation, and handling large datasets. You are comfortable with machine learning and image registration and programming for automation are highly desirable. Familiarity with x-ray imaging or synchrotron techniques is an advantage. The role requires initiative, strong problem-solving skills, and the ability to work collaboratively in a multidisciplinary team. Excellent communication skills and a commitment to high-quality, open research are essential. You will join a dynamic international group of engineers, clinicians, imaging scientists and computational experts working to create the world's highest-resolution atlas of human organs.
What we offerFor information about our rewards and benefits please visit
Our commitment to Equality, Diversity and InclusionAs London's Global University, we know diversity fosters creativity and innovation, and we want our community to represent the diversity of the world's talent. We are committed to equality of opportunity, to being fair and inclusive, and to being a place where we all belong. We therefore particularly encourage applications from candidates who are likely to be underrepresented in UCL's workforce. These include people from Black, Asian, and ethnic minority backgrounds; disabled people and LGBTQI+ people.
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Research Fellow: X-ray Imaging of Bio-Mechanics
2 weeks ago
London, Greater London, United Kingdom UCL Full time £43,981 - £52,586 per yearRef NumberB Professional ExpertiseResearch and Research SupportDepartmentUCL BEAMS (B04)LocationLondonWorking PatternFull timeSalary£43,981-£52,586Contract TypeFixed-termWorking TypeOn siteAvailable for SecondmentNoClosing Date04-Jan-2026About usUniversity College London (UCL) UCL is a multi-disciplinary university with a population of over 13,000 staff...
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