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and phylogenetic comparative analyses using R or Python Present research findings at scientific meetings and symposia Prepare and contribute to the publication of results in peer-reviewed journals Your
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placement locations. Advanced metaheuristic optimisation algorithms, implemented in Python and interfaced with DIgSILENT PowerFactory, will be developed to determine the most effective PST locations and
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skills, preferably Python Knowledge of machine learning Willingness to work on a cross-disciplinary project. *for students with an education earned outside of Sweden, a 4-year Bachelor’s degree is accepted
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settings, with 5+ years of experience building impactful deep learning systems A strong publication record in top-tier conferences such as NeurIPS, ICML, or ICLR Strong programming skills in Python and/or C
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fibre-optic sensing technologies and structural health monitoring Skills in data processing and numerical tools such as MATLAB or Python A high level of motivation, intellectual curiosity, and the ability
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into longitudinal studies and in using functional MRI and scripting-based languages (e.g. Matlab, R, Python). They must also have experience of conducting research with human participants and of performing highly
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analyse large, multidimensional 4D STEM datasets. Develop or adapt software tools (e.g. Python, MATLAB) for image reconstruction, phase mapping, and quantitative analysis of ferroelectric domain wall
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experience with programming tools such as R or Python. An interest in acquiring new data science and programming skills is required. A keen interest in teaching and academic development. An excellent academic
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include: Developing the model using open-source Python software Planning and conducting experiments Analysing teardown reports and experimental data Validating and improving the model Publishing results in
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principles. The candidates must also be able to quickly grasp emerging trends in the relevant discipline. The candidate should be willing to work using different programming languages/frameworks such as Python