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robotics and design journals/conferences. Essential Criteria PhD (or equivalent experience/Masters with significant research background) in a relevant field Extensive programming skills (e.g., C++, Python
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operation · Application of artificial intelligence or machine learning in energy or engineering systems 5. Strong programming and modelling skills using relevant tools such as Python, MATLAB
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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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related discipline and have begun to establish a strong research profile, evidenced by a strong, well-cited publication record. Proficient in Python, R, BASH and/or other relevant programming languages, you
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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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, 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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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
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conferences. It is essential that you hold a PhD/DPhil in computational biology, genomics, bioinformatics, computer science, statistics, or a related field together with strong programming skills in Python, R
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standard imaging analysis method including use of Python (NumPy/SciPy/PyTorch/Tensorflow), Matlab, C++, version control software (e.g. git), and statistical analysis using R, SQL, etc. Familiarity with