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computational scientific workflows. Experience with scientific programming (Python or similar) Experience working in Linux-based computational environments Documented experience with high-performance computing
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reproducible manner and contribute to publications, protocols, and internal know-how. The candidate should have Key Selection Criteria: Strong programming and in silico analysis skills (e.g. Python or similar
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programming, e.g., in C++, Python or Matlab. Who we are The successful candidate will be hosted by the Section on AI & Sound. This section is led by Prof. Jan Østergaard. A dedicated supervisory team composed
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development section, specifically: Develop and maintain custom Python graphical user interfaces that enhance the usability of the group’s research tools. Optimize data workflows through efficient data
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communication. Strong competences in mathematical modelling and simulation of flow, heat transfer and dynamic system behaviour, including use of tools such as MATLAB/Python and CFD. Strong hands-on experience
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, relevant data science skills, scraping, and coding in R and Python Experience with building and analyzing large datasets 5) Other preferred qualities The ability to independently organize and potentially
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Andres Masegosa (arma@cs.aau.dk), Department of Computer Science. (please see: https://andresmasegosa.github.io/ . The project’s domain PI is Professor Jamal Jokar Arsanjani (jja@plan.aau.dk), Department
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bioinformatics including NGS (Nanopore, Illumina, PacBio) Experience with automation and coding in Python or other programing languages Experience with protein software tools like AlphaFold3, Boltz2, PyMOL
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highly advantageous: Scientific programming in Python or MATLAB Probabilistic methods, Bayesian inference, or stochastic modelling Structural mechanics, material modelling, or multi-physics simulation Data
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: Scientific programming in Python or MATLAB Structural mechanics, reliability analysis, or probabilistic modelling Data analytics, SHM/SCADA data interpretation, or digital-twin technologies Wind energy systems