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structure modeling in cancer immunotherapy design. Profile A — AI PhD in machine learning, computer science, computational science, or a related field. Strong experience with deep learning (e.g., PyTorch
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systems and control theory, circuit theory, optimization, and machine learning, with the ultimate goal of advancing the mathematical foundations of physics-based learning. Your responsibilities include
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. (2) Prof. Francesca Grisoni (https://molecularmachinelearning.com/ ) leads the Molecular Machine Learning Group at the Technical University Eindhoven and will lead a project on designing potent cyclic
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, visualization, rendering, modeling, interaction, simulation, game technology, and immersive environments, with strong connections to artificial intelligence, data science, AR/VR, 3D computer vision, and high
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% of your time), including tutorials and supervision of Bachelor’s theses. This is what we ask of you This is an interdisciplinary project that combines machine learning and AI, probabilistic risk
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modeling, geometric deep learning or physics-informed machine learning, or you are willing to learn these quickly; strong collaboration skills: you enjoy working in a multidisciplinary team and feel
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paradigms. We are also leveraging several analytical tools such as computational modelling and machine learning. As a Research Assistant, you will help collect, analyse and interpret EEG data collected in
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Specific Requirements The ideal candidate has the following qualifications: - interest in human cognition - experience with neural data, especially EEG or MEG - experience with machine learning models
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learning pipelines for multilayer segmentation and nanoscale transistor classification from microscopy images; (b) Designing graph-based inference models capable of reconstructing higher-level logical blocks
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seeking a highly motivated Postdoctoral Researcher to join the Machine Learning cluster. The position is part of a research project investigating how visual foundation models can efficiently acquire new