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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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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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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
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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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downconversion layer Analysis of data using software tools such as MATLAB, Python, or Origin. The candidate must be familiar with materials studio software and any other materials modeling software. Experience in
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of field campaigns, data collection and lab work, Spectral data analysis, data processing, and model development, ‘R’, Python programming / package development, Co-supervise PhD and undergraduate students