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least 5 years of experience in software development, with a focus on RESTful APIs Technical Skills Proficiency in Python 3 (Flask/Django experience is a plus) Experience with Java and its ecosystem
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experience with HHG sources are a plus but not critical. Knowledge of programing languages such as Python (and with finite element simulations specifically) would be also valuable.
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modeling, meta-modeling, or statistical learning Strong programming skills in Python and/or C++ Familiarity with EDA tools, digital architecture, or embedded systems is a plus. In accordance with
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interest in historical research, migration, and digital infrastructures Familiarity with digital tools and languages such as Wikibase, SPARQL, RDF, Python, GitHub, and Jupyter Notebooks is highly desirable
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skills : We expect a candidate with a strong background in machine learning or statistics. The candidate must also be proficient in high-level languages like Python. Familiarity with single-cell date and
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/ NiFi/ Knime, Programming in Python and SQL. Experience with version control systems (Git, CI/CD); Java/Scala is a plus. Familiarity with containerisation and orchestration like Docker and Kubernetes
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++, Python or Java is desirable Excellent verbal and written communication skills. The working language of the laboratory is English. Experience in communicating research findings to a non-specialist audience
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, programming in Python, advanced vector data analysis software (e.g. Paraview), knowledge of condensed matter physics, magnetism and/or electron microscopy.
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experience with MTJ-based devices and magnetic/electrical characterization tools. • Knowledge in ion beam processes. • Fluency in data analysis (e.g. Python). • Excellent communication skills in English
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skills in C/C++ and Python Relevant experience in deep reinforcement learning A proactive attitude towards achieving research excellence Demonstrated commitment, teamwork abilities, and critical thinking