Research Fellow: Machine Learning for Multi-scale, X-ray Mapping of the Human Brain
Role details
Job location
Tech stack
Job description
Would 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 ( c.walsh.11@ucl.ac.uk) or Prof Peter Lee (peter.lee@ucl.ac.uk). For application process queries, contact Ruikang Xue (ruikang.xue@ucl.ac.uk).
Requirements
Do you have experience in Machine learning?, Do you have a Doctoral degree?, You 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.