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element method and/or spectral solvers Practical experience in at least one programming language (preferably Python) and experience with the use of Unix/Linux operating systems Structured and analytical
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, including familiarity with fundamental concepts such as public-key cryptography and security protocols. Experience with programming (e.g., Python, C/C++, or similar) and an understanding of networking
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for diagnostics and therapy Conduct comprehensive bioinformatic analysis utilising established methodologies and tools (e.g. R, Python, MATLAB and other relevant bioinformatics software packages) Collaborate
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Python) and data analysis or machine learning applied to materials science Ability to work in interdisciplinary project or industrial experience About the employment The employment is a temporary position
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the simulation models using appropriate tools (e.g., AnyLogic, Simio, Siemens Plant Sim, Python, MATLAB or other relevant simulation platforms) Evaluate and validate the proposed framework and assess its impact on
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.: +33 (0)4 76 88 22 80, email: schulli@esrf.fr ), Expected profile A background in X-ray diffraction or electronics would be desirable and knowledge of programming (Python) would be an advantage. Teamwork
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refer to https://www.uni.lu/snt-en/research-groups/sigcom/ . Your role The successful candidate will join the SIGCOM Research Group, led by Prof. Symeon Chatzinotas. This PhD project aims to develop
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Biomedical engineering Physics or Applied mathematics You present with expertise in advanced signal and data processing and its applications to cutting-edge imaging. Developing programming skills (Python, C
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analysis; strong letter of recommendation from master project supervisor; Beneficial skill: programming, including some languages of the following list: C, C++, Python, Matlab, Mathematica. Programming
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techniques e.g. laser and optical instrumentation; computational/numerical modelling programming skills e.g. Python, C++. Eligibility Open to both UK and International applicants, including EU applicants. How