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study design, scientific methods, and statistical modelling Python, C# or equivalent language expertise Basic knowledge of machine learning or deep learning Desirable Skills Exposure to musculoskeletal
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schools, where children and adolescent research participants will complete computer-based learning tasks designed to capture metacognitive monitoring and regulation during task performance. The successful
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reconstruction, data inference and fusion using classical and physics-informed machine learning approaches to advance time-resolved morphological and tissue property imaging of the heart The work will involve
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vehicles. Another research focus is on solid-state pulse modulators for medical applications (computer tomography/cancer treatment) and accelerators (CERN). For the design and optimisation of the various
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biomedical sciences. We are looking for candidates with A PhD in machine learning, computer science, computational biology, or a closely related field (completed or near completion). Demonstrated experience in
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sensors and usage logs using advanced statistical and machine learning approaches to develop personalised nudging and adaptive interventions. The candidate will also lead the development of a cross-platform
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, or design for manufacture is a plus. Programming and image-analysis skills, preferably in Python, and an interest in computervision, image processing, or machine learning. Experience with cameras
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be learned during the project, but solid Python skills and hands-on experience with graphs and GNNs are essential. Degree in computer science, software engineering, data science, machine learning
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; How you would handle longitudinal data and missing values; Which statistical and/or machine-learning methods you would consider How you would validate and interpret the results. No actual analysis is
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Building a quantum computer that can solve real-world problems will require the integration of many highly coherent qubits. Hole-spin qubits in planar germanium quantum wells are among the most