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Field
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qualifications Documented experience with data analysis and programming (e.g., Matlab, Python or R). Experience of risk assessment and/or decision analysis Experience of probabilistic methods such as Monte Carlo
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qualifications Marine biogeochemical processes Hydrodynamic processes related to ships, turbulence, or mixing Oceanographic modelling Data analysis and programming (e.g., MATLAB, Python, or R) Interdisciplinary
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, in vitro transcription, northern blotting, etc.). Knowledge of UNIX/Linux computing environments and of a programming language (e.g., Perl, Python, Rust, C++, R, etc.). We offer you in accordance with
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: university and, if applicable, PhD degree (e.g. Master/Diploma) in mathematics, physics, materials science or related subjects basic knowledge of computer programming (e.g. Python, Matlab and C++) excellent
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experience with algorithms relevant to computational biology documented programming skills, e.g. in Python and R very good communication and organizational skills with the ability to work to timelines, both
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meet the requirements for admission to the faculty of engineering's Doctoral Programme Good oral and written communication skills in English High level competency in GIS and Hydrology Field experience
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your research at conferences, workshops, and through scientific publications. Your profile: ▪ You hold an MSc degree in physics, engineering, or computer science. ▪ You are very experienced in Python
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, training, and collaboration Preferably a strong background in aircraft design and propulsion systems Preferably Proficient in programming (MATLAB preferred; Python is also acceptable) Prior experience with
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system analysis or comparable Initial experience in optimization or statistics is an advantage Initial experience of an object-oriented programming language (e.g. Python, Matlab) and MS Office Analytical
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-on fabrication of TEM supports and MEMS devices. You have good Python programming skills. Experience with cleanroom processes (lithography, etching) or MEMS is a plus. You are motivated to work in a