We are proud to announce that 3 globally recognized sites with pioneering roles in artificial intelligence are joining forces to build up a German-Canadian Helmholtz International Lab by merging the outstanding expertise in deep learning at Mila with computational genomics at Helmholtz Munich and integrate causal learning from MPI Tübingen. This is an exciting opportunity for successful candidates to be part of this unique collaboration.
For this position at Mila, we invite applications from highly motivated postdoc candidates with the passion for and experience in computational biology and machine learning to be part of this promising endeavour.
Mila (Quebec Artificial Intelligence Institute) is a community of more than 500 researchers specializing in machine learning and dedicated to scientific excellence and innovation. Mila’s mission is to be a global pole for scientific advances that inspires innovation and the development of AI for the benefit of all.
Helmholtz Munich is a research center with the mission to discover personalized medical solutions for the prevention and therapy of environmentally triggered diseases and promote a healthier society in a rapidly changing world. Helmholtz Munich belongs to Germany´s largest research association and is globally recognized for innovations in data science and applied machine learning through the Institute of Computational Biology (ICB) and Helmholtz AI and through the constantly growing AI ecosystem the metropolitan region of Munich offers.
Max Planck Institute Tübingen is a leading international research group working on topics in computer vision, machine learning, and computer graphics. The institute combines – within one center – theory, software, and hardware expertise in the research field of intelligent systems. The Tübingen campus focuses on how intelligent systems process information to perceive, act and learn through research in the areas of machine learning, computer vision, and human-scale robotics.
The outcome of this project endeavours the impact of our understanding of gene regulation and to allow the prediction of the effects of unseen cellular perturbations, such as drug responses, at the level of gene expression and beyond. At the same time, the project aims to contribute through machine learning and deep learning approaches to revolutionize modeling and prediction problems.
About the position at Mila:
- Starting Date: As early as possible
- Supervision: Yoshua Bengio
- Your tasks: research in machine learning applied to better modeling of cell dynamics, including its causal structure, effect of interventions (including of drugs).
- Your profile: experience in machine learning, in particular deep learning, ideally model-based reinforcement learning, temporal modelling or causality; exposure to biology (the more the better), in particular cell biology and computational genomics.
- We offer: a rich machine learning environment (Mila) with hundreds of peers working in closely related areas of machine learning, as well as the collaboration with the Helmholtz lab in Munich for the computational biology side; immersion in the smaller group led by Yoshua Bengio working on applications of ML in healthcare and drug discovery, as well as causal discovery.
- Contract period: 2 years, with funding available and a strong possibility to renew for a 3rd year.
How to apply:
- Please follow these guidelines – you will be asked to complete the Mila supervision request form.
- Please kindly identify that you are applying to the ‘Causal discovery of cell dynamics’ project in the last question of the application form.
Thank you and best of luck!