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Research Assistant/Associate in Machine Learning (Fixed Term)

Closing date: 
Thursday, 23 December 2021

Department of Engineering

We are seeking a Postdoctoral Research Assistant/Associate to join the Machine Learning Group (http://mlg.eng.cam.ac.uk) in the Department of Engineering, University of Cambridge, UK. This position will contribute to the research programme "Machine Learning for Molecular Design", which is funded by UKRI through a Turing AI Acceleration Fellowship.

The programme's goal is to accelerate the molecule discovery process by creating fundamental contributions in the area of machine learning for molecules. Impact areas include materials science and drug discovery.

The Research Assistant/Associate will work with Dr. José Miguel Hernández Lobato and other members of the Cambridge Machine Learning Group (http://mlg.eng.cam.ac.uk/). The project also offers collaborations with Prof. Rafael Gomez-Bombarelli (MIT), Prof. Matthew J. Gaunt (University of Cambridge), Dr. Marwin Segler (Microsoft Research), Dr. Ola Engkvist (AstraZeneca) and Prof. Markus Reiher (ETHZ).

Key responsibilities include working on deep learning, probabilistic modeling, Bayesian methods, deep generative modeling, reinforcement learning and graph neural networks.

Additional responsibilities include developing research objectives and proposals; presentations and publications; assisting with teaching; liaising and networking with colleagues and students; planning and organising research resources and workshops.

https://www.jobs.cam.ac.uk/job/32318/

About us

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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