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an exceptional international team with expertise in all aspects of the project. Your tasks will include: • Preparation of different EO and in-situ datasets for training a machine learning model • Development of ML
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expert knowledge in a reusable format. Numerical Representation, Develop numerical representations of ship designs that are interpretable by machine learning algorithms and suitable for generative ai model
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. Fe, S) on CNT purity and structure. Evaluate CNTs as conductive additives in standard Li-ion battery electrodes. Apply AI/machine learning to optimise experimental design and growth parameters
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: electronic structure calculations (plane wave DFT if possible), statistical thermodynamics, molecular dynamics. Skills in Python, bash scripting, Fortran 90 and machine-learning would be appreciated. The PIIM
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of potentially novel modes of protein binding is possible in collaboration with other members of the lab. Desired (but not absolutely required) skills: programming in python, machine learning, and experience in
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approaches that integrate both qualitative and quantitative research (e.g., combining big data or machine learning with in-depth fieldwork) can also be pursued. Method selection and mastery are viewed as part
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proactively. Experience in design, prototyping, basic programming, AI and/or machine learning are a plus. International PhD candidates with scholarships below the applicable IND income standard (currently
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, pharmacology, inflammation, cancer and neurobiology. We also teach students studying at various programs and independent courses in cell biology, physiology, neurobiology, anatomy and histology
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and small, contribute to a better world. We look forward to receiving your application! Your work assignments We are looking for one PhD student working on generative AI/machine learning, with
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well as digital filters is advantageous. Your workplace You will be working at the Division of Electronics and Computer Engineering (ELDA), which conducts teaching and research in a broad range of areas, from