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Strong background in differential equations and numerical methods Solid programming skills e.g. Python, C++, Julia or similar Interest in interdisciplinary research bridging mathematics and environmental
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novel machine-learning methodologies Excellent programming skills in Python and familiarity with modern ML tooling and reproducible research practices Experience training and deploying machine-learning
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- good command of at least one TCAD tool (e.g. Sentaurus) - experience in processing data (ideally in Python) or/and experience with AI methods - A very good level of oral/written expression in English
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learning applied to dynamic systems; Proficiency in key machine learning libraries (PyTorch, JAX, etc.); Mastery of Python and the software ecosystem for scientific data analysis and management (NumPy
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Familiarity with omics approaches such as scRNA-seq, proteomics Programming or data analysis skills such as R, Python, or similar Experience in international collaborative projects Experience with laboratory
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in nanomagnetism and spintronics with emphasis on magnetic skyrmions - Expertise in electrical and MOKE measurements - Expertise in micromagnetic simulations - Experience with Python - Micro/nano
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of Research Experience1 - 4 Additional Information Eligibility criteria - Publish scientific results - Exchanges with international scientific colleagues - Statistics and skills in programming (Python, Matlab
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development and data analysis will be required. A solid knowledge of Python and/or C++ is also essential for this position. Finally, a good command of spoken and written English is required. Additional comments
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++ and/or Python Experience with SOFA, FEniCSx or similar simulation frameworks is a strong plus Motivation to work at the crossroads of mechanics, AI and medical technology, in close collaboration with
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datasets, and strong programming in Python and C. Familiarity with galaxy-redshift survey or 21-cm data analysis is a plus. The successful candidate will join the cosmology and astroparticle team at LAPTh