A post-doctoral Research Associate or Assistant position in Machine Learning for Precision Mental Health is available to work with Prof Zoe Kourtzi at the Adaptive Brain Lab, Univ of Cambridge, UK (http://www.abg.psychol.cam.ac.uk) and Prof Carola Schönlieb at the Cambridge Image Analysis Group, Department of Applied Mathematics and Theoretical Physics, University of Cambridge.
The position will focus on the development and implementation of state-of-the-art machine learning approaches and image analysis techniques for early diagnosis of mental health disorders (e.g. dementia, mood-related disorders). The research will involve mining biological (brain imaging, genetic) and cognitive data from large-scale cohort studies with advanced machine learning methods to determine markers for early disease diagnosis. The aim of the research is to develop biologically-inspired artificial systems for precision mental health by bringing together expertise in machine learning, data science, neuroscience, and clinical practice.
The successful applicant will receive multi-disciplinary research training at the interface between machine learning, neuroscience, and clinical translation and will work in collaboration with The Centre for Mathematical Imaging in Healthcare, and the Alan Turing Institute, the UK's national Institute for Artificial Intelligence and Data Science.
Applicants should have a PhD, Masters and/or First Degree, together with a strong academic track record, in a relevant area (e.g., Mathematics, Computer Science, Engineering, Neuroscience, Medicine). Programming skills are highly desirable and experience with machine learning and data science are highly beneficial.
Fixed-term: The funds for this post are available for 1 years in the first instance.
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Please note the closing date for applications is 4 February 2020. Applications received after this time will not be considered.
Please quote reference PJ21907 on your application and in any correspondence about this vacancy.
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