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the controlled flow at tunable temperature and photopolymerization of the precursor. The practical work will be complemented by fluid mechanics computer simulations, including solutions employing machine learning
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, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks Requirements: excellent university degree (master or comparable) in computer engineering or electrical
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-driven approaches to health, society, and policy. BISI combines expertise in epidemiology, biostatistics, health economics, and machine learning to tackle complex societal challenges. BISI is actively
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need expert knowledge in bioinformatic data analysis. Strong expertise in multi-omics data analysis (using R and Python) and a deep understanding of machine-learning models are must-criteria
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for the modeling and simulation of 3D reconfigurable architectures e.g. based on emerging technologies (e.g. RFETs, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks
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critical component analysis, and (iii) development of Automation of ML model and data selection. The applicants should have knowledge of machine learning and optical networks and willing to engage in testbed
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Research theme: Fluid Mechanics, Machine Learning, Ocean Waves, Ocean Environment, Renewable Energy, Nonlinear Systems How to apply: How many positions: 1 Funding will cover UK tuition fees and tax
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of robotics, electromobility and autonomous driving. We offer advanced PhD courses where we extend the fundamentals in optimal control, machine learning, probability theory and similar. The research and
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We are seeking a highly motivated PhD candidate with a strong interest or background in AI as well as in one or more of the following areas: Generative AI, Natural Language Processing, Deep learning
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., machine learning, stochastic dynamic programming, simulation). Affinity with (food) supply chain management is preferred. To collaborate with and to co-supervise MSc thesis students and internship students