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. The consortium consists of world-class scientists with competences spanning chemistry, biochemistry, computer science, and machine learning. All fifteen doctoral candidates will work with two research groups, and
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-liquid crystal order in developing cross-striated muscle, or use machine-learning to expand existing custom-built image analysis pipelines (Python, Matlab). To learn more about this project, we highly
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defects. The charge transport will be implemented stochastically to mimic nature. A significant focus of the project will be to apply machine learning techniques to optimize the model and enable charge
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interest for the machine learning and neuroscience communities How to apply... Applications should include: Curriculum Vitae Cover letter Early application is highly encouraged, as the applications will be
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knowledge and/or experience in several of the following topics: Optimisation algorithms Machine learning algorithms Swarm intelligence Algorithmics Parallel/Distributed computing Space systems engineering
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discipline The ideal candidate should have some knowledge and/or experience in several of the following topics: Optimisation algorithms Machine learning algorithms Algorithmics Smart buildings Internet
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, or any related engineering discipline The ideal candidate should have some knowledge and/or experience in several of the following topics: (Quantum) Optimisation algorithms (Quantum) Machine learning
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for each position. PhD position in Advanced Lipid-Based Cellular Membrane Mimicry and Interaction Studies PhD position in Holographic Duality and Machine Learning PhD position in Next-Generation Nanomaterial
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PhD candidate in the automated detection of measurable residual disease in hematological malignancie
(deep learning, probabilistic modelling, generative AI) or machine learning Proficient in Python or R programming Strong communication skills in English Strong interpersonal skills Ability to work