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Institute (IvI) and which is a cross-institute collaboration at the Faculty of Science aimed at bridging the gap between modern machine learning developments and their applications to the different areas
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distributed devices (smartphones, wearables) to learn from new data streams over time (Continual Learning) while collaborating globally (Federated Learning). Analyze Mobile & Wearable Data: You will work with
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part of the ESDiT programme on the ethics of SDTs (see below), specifically a research line in ESDiT on methodological innovation, and involves close collaboration with another postdoc working
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provides opportunities to strengthen your academic profile through (co-) supervision of PhD, MSc, and BSc students, as well as teaching (if desired). Especially attractive is the opportunity to collaborate
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industrial design engineering. Together, we learn by making, creating, and innovating, addressing challenges in a solution-oriented way. Quality, connection and inclusivity are the foundation of our culture
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to develop generative AI methods for nanoparticle drug delivery design, at the intersection of machine learning, explainability, and pharmaceutical nanotechnology. Job description We are looking for a
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remains a major scientific and technological challenge. Your job This collaborative project between the Alta and Thevenon groups aims to address this challenge by developing molecular additives
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research group focused on (noncommutative) algebraic geometry, with connections to representation theory. This position offers opportunities for collaboration, participation in seminars and workshops, and
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to ESA’s strategy; a wide network of relationships and collaboration with top academics, industry and research centres; the opportunity to contribute to the Φ-lab strategy and activities. As an internal
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extensive knowledge on zooplankton imaging techniques ability to program and train machine learning models for automated image classification experience with shipborne campaigns and ready to join multi-week