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: PhD in solar energy, electrical engineering, or environmental sciences. Proficiency in PV systems, instrumentation, and performance measurement. Experience in processing environmental data (Python, R
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to the position, including demonstrated independent research and peer-reviewed publications. Proficiency in statistical programming (e.g., R, Python, or similar) is a requirement, as is fluency in spoken and
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have an interest in the use of AI in healthcare. Proven competence in programming methods in Python and similar environments is also essential. Informal enquiries may be addressed to Professor David
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methods in Python and similar environments is also essential. Informal enquiries may be addressed to Professor David Clifton (email: david.clifton@eng.ox.ac.uk). Only online applications received before
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-based experiments. Proficiency with scientific programming languages and analysis tools such as C++, Python, Geant4, and ROOT. Experience with simulation and modeling of detector systems and physics
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dynamics, and materials chemistry. Strong Python programming skills are required, and prior experience with developing open-source software or databases will be considered a plus.Candidates should apply at
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preferred. Strong data analysis skills and ability in programming languages, such as Python, for performing experiments and analyzing data. Knowledge of innovative phase retrieval algorithms is desirable
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., NeurIPS, ICML, ACL, EMNLP, etc.). Proficiency in programming languages such as Python, and experience with deep learning frameworks like TensorFlow, PyTorch, or JAX. In-depth understanding of transformer
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not have exceeded two years previous work at the postdoctoral level at start of appointment. Coding experience in a scientific computing language is desirable (e.g., Python, MATLAB, R, IDL, Fortran, etc
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programming of algorithms. The use of programming languages such as Python, R, SQL, and C++ will be a daily part of the project, and proficiency in these languages is required. However, additional datasets will