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representing transcription reaction networks, enzyme kinetics, and transport phenomena. Simulate mRNA production in enzymatic tubular reactors using MATLAB, Python, or related computational tools. Prepare
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, or industrial engineering. Proficiency in Python and simulation tools (e.g. AnyLogic, Arena) and optimization solvers (Gurobi, CPLEX). Solid background in decarbonization modeling, logistics, and techno-economic
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, energy systems, simulation, and/or transportation research. Technical skills: Python programming; simulation. Domain knowledge: Decarbonization modeling, life-cycle assessment, battery-electric vehicle
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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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and solids. Experience in scientific programming in C/C++, Python, Fortran, Mathematica or similar is required. The successful candidate will either hold a PhD in Physics or a related area, or
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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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: 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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and strong experience with the Python library JAX would be a plus. Experience writing and publishing academic papers. Please see job description for a full list of requirements. *Candidates who have not
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and programming skills (Python preferred). Excellent written and verbal communication in English. Passion for exploring the frontiers of condensed matter physics. What We Offer · Pioneering