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/DPhil) together with established knowledge in wired computer networks and sustainable computing, significant coding experience (both Python and C/C++), and a record of working in a Linux environment and
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doctoral studies / focus on solid state physics or chemical physics Professional skills: Development of ab initio methods Methodological skills: Python, Fortran, C, C++ High performance computing Good
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Crainio system performance. The ideal candidate has expertise in Python and biomedical signal processing, more specifically optical signals like Near-infrared Spectroscopy and Photoplethysmography. Strong
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area, with content covering robotics and machine learning, and excellent programming skills in Python. You should have research experience in either robotics or machine learning. You should also have
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, skills, and achievements in meeting (or the potential to meet) the criteria set out below indicating which post is being applied for. Next Steps Short-listed candidates will be invited to the University
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Control engineering (experience with nonlinear systems is a plus) Machine learning and deep learning in context of physical systems Programming skills are required, with Python experience preferred. A good
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, digital twins, or related areas Excellent publication record in high-quality journals and/or conference proceedings Excellent programming skills, particularly in Python and/or C/C++; hands-on experience
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-centred AI, digital twins, or related areas 3. Excellent publication record in high-quality journals and/or conference proceedings 4. Excellent programming skills, particularly in Python and/or C
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with R or Python tools. Experience in processing of targeted and untargeted mass spectrometry datasets Demonstrated research competence and initiative through inernational publications in peer-reviewed
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in Environmental Modelling, Land Use modelling or another relevant field, with clear skills highly complementary to those of the JPP4JL research team Proven ability to write code in R or python