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description You will join an excellent team and collaborate with a diverse group of people working in the field of Robotics and AI. Duties Software-focused Translate existing MATLAB code to Python/C++. Develop
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challenges, and we are currently moving the code to a new python based High Performance Computing enabled modelling framework. This is an exciting opportunity to contribute to a high-impact scientific codebase
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competitive level. Proficiency in a scripting language like R or Python, as well as ability to work efficiently in a Linux command-line environment and on high performance computer clusters. Excellent
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characterization (SEM, EDX, etc) Aerosol physics Data analysis and programming (e.g., MATLAB, Python, or R) Interdisciplinary teamwork Fieldwork and particle sampling e.g. on/from vehicles Swedish language skills
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. Requirements A doctoral degree related to Data Science, involving applied work in machine learning Experience with common ML frameworks (e.g., Tensorflow, PyTorch) Expert knowledge of Python or C/C++ Experience
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, mathematics, or a related field. Ability to independently conduct large-scale genetic analyses (GWAS). Expertise in bioinformatics/statistics, including programming (e.g., R or Python). We are searching
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competence in Python and Matlab The ability to work independently Good written and oral communication skills in English Contract terms Type of position: Full-time research position Duration: Three months Start
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instrumentation at hard X-ray spectroscopy beamline Leading instrument development projects Combined XAS and X-ray diffraction, including XRD analysis Python programming for data reduction, gui and analysis
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, motivation and flexibility at work. Meritorious for the position are: Good programming skills (eg R and/or Python). Miscellaneous The employment is time-limited for one year, however at the latest until on 30
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of projects could also be included. Work can include, but is not limited to, development of pipelines in Nextflow or Snakemake, scripting in Python and/or R, and running large-scale analyses efficiently in HPC