Post-doc position on grey-box machine learning (closed)
10.1.2024The Data Mining and Machine Learning group (http://dmml.ch/) at the University of Applied Sciences in Geneva has an opening for a full-time post-doc position. The research target is to develop grey-box (hybrid) machine learning methods that combine data-driven models such as deep neural nets and theory-driven, physical and/or causal models . By combining these ...
Read more2022 Retrospective
7.3.2023The year 2022 is at its last days, and this is a good opportunity for wrapping up the activities of our group, as they occurred within 2022. 2022 was a very refreshing year for the DMML group, and the following points will justify why! First and foremost, our team had the pleasure to welcome three new, inspiring ...
Read moreFour new research projects!
28.11.2022The second half of 2022 has been very exiting! Our team has kicked-off 4 new research projects. In short, the projects are the following ones: EO4EU: a Horizon Europe project related to Earth Observation Automated Bridge Defect Recognition: an Innosuisse project regarding bridge inspection and ML-driven damage detection. Learning generative models for molecules: An SNF project (Project funding, division ...
Read moreDmml is growing by the addition of three new team members
7.3.2023We are delighted to announce that our team has grown, as three new members have joined us within the last months. Dr. Nils Schaetti has joined our team this Fall. Nils holds a PhD from the University of Neuchâtel and has both academic experience, as a postdoc at UNIGE, as well as industrial experience. He will ...
Read moreResearch visits and international collaborations in our group
27.8.2025The last couple of weeks have been very vivid for our group, as we had the pleasure of welcoming two esteemed fellow researchers that visited us, Mr. Antoine Wehenkel from the University of Liège (Belgium) and Ms. Aicha Karite from the German Aerospace Center (DLR). The collaboration with Mr. Antoine Wehenkel and his group at the ...
Read morePost-doc position on generative models for inverse problems and simulation-based inference (Closed position).
30.1.2023We have an opening for a full-time post-doc position. The research target is to develop machine learning methods to solve inverse problems accounting for the inherent uncertainty of the inverse problem. We will formulate these problems as inference problems with prior scientific knowledge available in the form of simulators. We will follow the simulation-based inference ...
Read morePhD position on generative models for inverse problems and simulation-based inference (Closed position).
30.1.2023We have an opening for a PhD position. The research target is to develop machine learning methods to solve inverse problems accounting for the inherent uncertainty of the inverse problem. We will formulate these problems as inference problems with prior scientific knowledge available in the form of simulators. We will follow the simulation-based inference paradighm ...
Read morePost-doc position on generative models for discrete data structures (Closed position)
30.1.2023We have an opening for a full-time post-doc position on a research project on the development of generative models for discrete data structures, such as graphs and in particular molecules. We seek to develop generative models capable of conditional generation as well as what can be considered the equivalent of style transfer for discrete structures. ...
Read morePhD position on generative models for discrete data structures (Closed position)
30.1.2023We have an opening for a PhD position. The research target is the development of deep generative models for discrete data structures such as graphs and in particular molecules. We seek to develop generative models capable of conditional generation as well as what can be considered the equivalent of style transfer for discrete structures. The successful ...
Read moreLiBertaS: New research project funded by the Halser Foundation
20.4.2022We are very pleased to announce that the Hasler Foundation has approved the project proposal of Dr. Grigorios Anagnostopoulos, and will fund the project "LiBertaS". LiBertaS aims to liberate the access of Location Based Services (LBS) to the highly accurate fingerprinting methods in business practice, by greatly downscaling the data volume needed for their operation. ...
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