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Tag Archives: machine learning
Learning generative models for molecules
Drug discovery is a well-known and challenging problem. Typically, one needs to navigate through a vast chemical space of up to \( 10^{60} \) small organic molecules to find a potential drug candidate with desired properties. Such a trial-and-error process … Continue reading
Posted in projects
Tagged generative modeling, graph network, machine learning, research project, snsf
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Automated Bridge Defect Recognition
Infrastructure assets, such as bridges, need to be inspected regularly. Our objective is to reduce the need for human involvement, minimize risks to health and safety, decrease the impact of subjective engineering assessments, digitize asset management, and promote sustainable inspection … Continue reading
Posted in projects
Tagged Bridge Defect Detection, Contrastive Learning, innossuise, LeanBI, machine learning, research project, Self-supervised learning
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MIGRATE – A Multidisciplinary and InteGRated Approach for geoThermal Exploration
To mitigate climate change, our society must reduce its carbon footprint coming from fossil fuel energies and favor green energy solutions instead. Geothermal energy is a resource this available in abundance. However, the development of this sector is hindered by … Continue reading
Posted in projects
Tagged machine learning, research project, snsf
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Interpretable Condition Monitoring for Complex Engineering Systems
Just as it is important for us to monitor our own body in order to maintain good health, we should have an accurate understanding of the state of engineering systems in order to prevent failures. In this project, entitled "Interpretable … Continue reading
Posted in projects
Tagged machine learning, Naoya Takeshi, research project, snsf
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Post-doc position on grey-box machine learning (closed)
The 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 … Continue reading
Posted in news, recruitment
Tagged Alexandros Kalousis, dmm, machine learning, Naoy Takeishi, postdoc, project, recruitment, research project, snsf
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Research visits and international collaborations in our group
The 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 … Continue reading
Posted in news
Tagged Aicha Karite, Alexandros Kalousis, Antoine Wehenkel, Grigorios G. Anagostopoulos, IPIN, IPIN conference, localization, machine learning, Naoy Takeishi, NeurIPS, positioning, SimGait, simulation-based inference
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PhD student position, University of Geneva (Computer Science) and University of Applied Sciences (Closed position)
We have an opening for a PhD position. The research target is the development of deep generative models that can incorporate strong domain knowledge within the learning process. Such domain knowledge, typically available in scientific fields, can be encoded in … Continue reading
Posted in recruitment
Tagged deep leaning, generative modeling, job openings, machine learning, phd, phd in machine learning, phd student
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Statistical Learning Workshop – Tentative program available
The tentative program of the Statistical Learning Workshop, which takes place on-line the whole day of the 18th of September, is now available on the workshop's site http://dmml.ch/statistical-learning-workshop/!
Posted in news
Tagged invited talk, machine learning, phd student, presentation, statistical learning, Talk, workshop
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Statistical Learning Workshop – 18 September 2020
In this workshop we bring together the research communities of statistics and machine learning to foster a discussion between the two fields and develop research synergies. The workshop takes place on-line the whole day of 18/September. Depending on the COVID-19 status at the time a restricted physical presence version might also take place.
Posted in news
Tagged invited talk, machine learning, Seminar, statistical learning, statistics, Talk, workshop
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Multiple PhD positions in machine learning with simulation and physics modeling of the world (closed)
We have several PhD openings in machine learning research for exploring methods to combine learning with process-driven modeling and simulations. 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 behaviours in order to trigger early alerts. In chemoinformatics, an external system (e.g. RDKit) can provide relevant constraints for generating valid new molecules with specific required characteristics.
Posted in recruitment
Tagged deep leaning, job openings, machine learning, phd, phd in machine learning, phd student, recruitment
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