PhD Positions in Machine Learning at University of Geneva

PhD Positions in Machine Learning at University of Geneva

The successful candidate will enroll as a Ph.D. student in the Computer Science department of the University of Geneva (under the co-direction of Prof. Alexandros Kalousis and Prof. Stephane Marchand-Maillet) and, at the same time, will become a member of the Data Mining and Machine Learning group ( as a research and teaching assistant at HES-SO, Geneva. The positions shall be filled in as soon as possible.

The interaction and cooperation between a simulator and a machine learning model can be exploited in a number of areas where data are expensive or difficult to obtain, and/or where domain knowledge within the process-driven models can back the inductive biases factored into the machine learning models.
In the medical domain, machine learning methods can be combined with neuromechanical simulators to develop models of human locomotion that shall support critical medical decisions related to surgical interventions treating pathological gait patterns. In industrial manufacturing, simulations and physical modeling of realistic or extreme operational conditions can support the learning of rare faulty behaviors in order to trigger early alerts. In chemoinformatics, an external system (e.g. RDKit) can provide relevant constraints for generating valid new molecules with specifically required characteristics.

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PhD Positions in Machine Learning at University of Geneva

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