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Research Associate in Machine Learning for Brain and Mental Health (Fixed Term)

Closing date: 
Monday, 3 January 2022

Department of Applied Mathematics and Theoretical Physics

Applications are invited for a Research Associate position in Machine Learning for Brain and Mental Health to work with Prof Carola-Bibiane Schönlieb in the Cambridge Image Analysis Group, Department of Applied Mathematics and Theoretical Physics, and Prof Zoe Kourtzi at the Adaptive Brain Lab (http://www.abg.psychol.cam.ac.uk) University of Cambridge.

The position will focus on the development and implementation of state-of-the-art machine learning and image analysis techniques for the early diagnosis of mental health disorders (e.g. dementia, mood-related disorders). The research aims to develop biologically-inspired artificial systems for precision brain and mental health by bringing together expertise in machine learning, data science, neuroscience, and clinical practice.

Duties include developing and conducting individual and collaborative research objectives, proposals and projects. The role holder will be expected to plan and manage their own research and administration, with guidance if required, and to assist in the preparation of proposals and applications to external bodies. You must be able to communicate material of a technical nature and be able to build internal and external contacts. You may be asked to assist in the supervision of student projects, the development of student research skills, provide instruction or plan/deliver seminars relating to the research area.

Research Associate in Machine Learning for Brain and Mental Health (Fixed Term) - Job Opportunities - University of Cambridge

 

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The Cambridge Centre for Data-Driven Discovery (C2D3) brings together researchers and expertise from across the academic departments and industry to drive research into the analysis, understanding and use of data science and AI. C2D3 is an Interdisciplinary Research Centre at the University of Cambridge.

  • Supports and connects the growing data science and AI research community 
  • Builds research capacity in data science and AI to tackle complex issues 
  • Drives new research challenges through collaborative research projects 
  • Promotes and provides opportunities for knowledge transfer 
  • Identifies and provides training courses for students, academics, industry and the third sector 
  • Serves as a gateway for external organisations 

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