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Field
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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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(e.g. C++, Python, Matlab) OpenFOAM (beneficial, not required) Strong analytical and problem-solving skills. Approval and Enrolment The scholarship for the PhD degree is subject to academic approval, and
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manufacturing systems for subtractive manufacturing. Strong knowledge of process monitoring, manufacturing metrology, and programming tools such as Matlab is highly desirable. You should have good analytical
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, or Matlab). The student should also have a basic knowledge of statistics and an interest and enthusiasm for weather-energy and climate energy links. Support: The student will have weekly meetings with
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degree (2.1 +/MSc) in mechanical / civil / environmental engineering, physics or a related quantitative field; strong computing skills (Python/MATLAB/GIS); interest in transport or urban futures. Position
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. Experience in modeling biological processes. Experience in use of process simulation tools such as Matlab, Aquasim, Superpro Designer or similar. Expertise within fermentation technology and/or gas
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. Strong quantitative skills, with experience in econometrics and statistical analysis. Experience working with large datasets and appropriate software (e.g., Stata, R, Python, Julia, MATLAB). Excellent
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-oriented way of working A distinct advantage would be: Experience with data analysis and scientific programming (e.g. Origin, Igor Pro, Python, Matlab, Mathematica) A good command of written and spoken
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strain engineering is a plus. Data analysis skills (e.g. in Python, MATLAB or similar) are a plus. Excellent communication skills in English, both written and spoken Strong motivation to work
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(e.g., Python, or MATLAB, or C++; knowledge in ROS). Interest in robot control, learning, manipulation, and task planning. Preferred Experience with robotic hardware or simulation tools. Publications in