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knowledge of MATLAB/Python and signals processing Understanding of electromagnetics Genuine interest in battery technologies Experience with CAD and mechanical design How to apply: Interested candidates
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Computer Engineering, Engineering Physics, Aerospace Engineering or related areas. Basic knowledge of electromagnetics/RF. MATLAB/Python, RF instrumentation, electromagnetic simulation (CST or HFSS), 3D
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an equivalent field.b) Experience with Python programming Additional Information Benefits Monthly Maintenance Allowance: €1,090.98 Funding Entity: Instituto Superior Técnico (IST) Operational Programme: Compete
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, or computer science. Core competencies: solid background in quantum many-body physics strong programming skills (Python required, Rust a plus) experience with tensor networks, variational Monte-Carlo, machine learning
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 8 days ago
# Semiconductor processing and ion implantation # Nanofabrication and cleanroom technologies # Optical spectroscopy # Programming and scientific data analysis (e.g. Python, MATLAB) # Strong analytical and problem
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with experience applying these models to practical applications for real-world challenges. Good programming skills, Python is mandatory, other languages (e.g., Java, C++) will be considered a plus to
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Python and/or Julia using LINUX-based OS. Communication of findings through journal publications, conference presentations and project reports. Candidate Requirements Applicants must satisfy the criteria
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, specifically with Python-based engineering software development and hardware interfacing. Excellent oral and written English skills Demonstrated ability to independently conduct engineering projects Demonstrated
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validating mechatronic systems. Experimental methods and testing Programming and software development, specifically with Python-based engineering software development and hardware interfacing. Excellent oral
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. Ability to develop, understand, and critically evaluate machine learning research software, preferably using Python and PyTorch. An interest in foundation models, self supervised learning, multimodal