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and communication. Additional qualifications Relevant postdoctoral studies or equivalent industry experience are a strong merit but not a requirement. Programming knowledge in Python, and experience
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skills using statistical computing and visualization tools (e.g. R, Python or similar) are also considered a merit. The ability to handle large analytical datasets and to work in a structured and
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if the candidate has skills in programming languages (e.g. python, R), has experience in fieldwork and has a driving licence. In the recruitment process we will place great emphasis on the candidate’s
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, mixed-effects modeling, Bayesian methods, deep learning, variational autoencoders, generative AI). Is an experienced programmer in R and/or Python, and used to working with large datasets and reproducible
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required to meet the eligibility criteria. Of secondary importance are: Experience with Python and relevant libraries for machine learning, optimization and simulation. Documented expertise in simulation
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of robot cells, for example in RobotStudio, and digital twins. Good knowledge in configuration, programming and commissioning of industrial robots and associated software. Good programming skills in Python
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of biomass conversion technologies. Experience in programming with Python. Experience in Life Cycle Assessment. Experience in techno-economic analysis. Experience in scientific writing and communication
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applied perspectives. Strong programming skills in R, MATLAB, and Python are highly desirable. The successful candidate is expected to be fluent in English and open to both national and international
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of experimental spectroscopy or diffraction techniques such as XAS, XRD, FTIR, and XPS, of molecular modeling (MD/MC, DFT), and familiarity with basic programming (Python, MATLAB) and the use of Linux/HPC systems
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Good knowledge of scripting and automation (e.g. Python or Bash) Strong interest in developing further within the field Excellent collaboration and communication skills Ability to work independently and