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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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., 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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, 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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in programming (Python, Julia) (provide evidence with specific examples). Experience with statistical modelling and experimental design. Ability to work in a multidisciplinary team. Strong written and
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Python programming and familiarity with ML frameworks such as TensorFlow, PyTorch, or JAX. Experience with cheminformatics tools (e.g., RDKit, Open Babel) and chemical reaction databases (e.g., Reaxys
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machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Hands-on expertise in programming languages such as Python, R, or MATLAB. Solid understanding of battery systems, electrochemical
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publication record in high impact conferences / journals. Very good programming skills (e.g., C, C++, Python), familiarity with Linux. Proficiency in English and ability to work in a team. Outstanding
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for data science (Python, R, SQL, PostGIS, GeoPandas, etc.). Knowledge of urban models and spatial analysis tools (urban growth models, accessibility, change detection, etc.). Ability to work with
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methods. Programming languages, i.e. Python, Matlab, ... Level of experience evidenced by publications in peer-reviewed journals. Fluent in French and English. Experience of working as a member of a