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experience in the following fields. Cyber-physical modelling and simulation Digital Twins Autonomous Agents and Multi-Agent Systems Machine Learning and MLOps Probability & Statistics incl. Python/R Place of
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written and spoken English. Fluent in a computer coding language (python or Matlab or C++ or etc). The Scientific environment We offer creative and stimulating working conditions in a dynamic and
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., linear algebra, statistics, optimization, and calculus) is expected, along with programming experience using deep learning frameworks in Python (e.g., PyTorch). While prior knowledge of machine learning
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. Documented experience with any project in the blue bioeconomy domain, with Life Cycle Assessment, and with programming for data science(R, python) will be considered a strong plus. Proficiency in English is a
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protein design programs and analysis tools is crucial. Knowledge of programs like Rosetta, RF-diffusion, FoldX and python is necessary. Apart from very good modeling skills, knowledge in protein production
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, preferably Reinforcement Learning (e.g., Q-learning, Deep Q-Networks) or other control algorithms. Proficiency in Python, MATLAB, or similar for data analysis, modeling, or AI implementation. Strong written
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simulation software, such as TRNSYS, Modelica, EnergyPro Programming languages, such as Python Ability to communicate results in technical reports, and prepare scientific papers for publication in
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. The required selection criteria include: Knowledge of building physics and HVAC system Experience in advanced controls (e.g., RL, MPC) Programming knowledge (e.g., Python, R, MATLAB) Experience in built
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Research, Computer Science, Mathematics, Applied Mathematics, or related fields. Proficiency in programming languages such as Python, R, or other programming languages. Familiarity with multi-agent systems
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also be able to demonstrate excellent ability to code with or learn computer programming languages, such as C++, C#, Python, and/or Matlab. A desire to engage in cross-disciplinary research