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Field
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one of the following analysis techniques (multiple preferred): normative modelling, dimensionality reduction techniques, machine learning, deep-learning, state space modelling, advanced statistics
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record proven by relevant experience, publications, etc. The applicant is expected to have: MSc degree in Computer Science, Electrical Engineering, Cryptography, Applied Mathematics, or related field
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. In particular, the research project will focus on inferring trajectories from spatial transcriptomics data modelling at the same time the cells evolution in gene expression and in space. Required
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theories and numerical methods, carrying out and analysing field and remote sensing observations and conducting and analysing numerical model simulations. The PhD position is funded by the German Research
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background in Computer Science, Informatics Engineering, Mathematical Modeling, Computational Urban Science, Transport Modeling or equivalent, or a similar degree with an academic level equivalent to a two
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and competitions. The University of Bristol seeks an aspiring researcher with an engineering, physical sciences or mathematical background and an aptitude for practical implementation of cutting edge
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activity, oxygen storage capacity), in collaboration with machine learning experts to build predictive models. Producing well-characterized nanoparticle batches for external testing and catalytic
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The project: The deployment of generative AI—particularly Large Language Models (LLMs) based on transformer architectures—in industrial settings poses several critical challenges. Ensuring reliable
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Specifications. The PhD topic consists of two parts, the weighting of which can be adjusted. First, natural frequencies of different UAV categories for different power settings shall be modelled. Second, based
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Master’s degree in Applied Mechanics, Mechanical Engineering, or a closely related field. Strong knowledge of fluid mechanics, CFD, turbulence modelling, and structural mechanics. Understanding