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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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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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experience of application of artificial intelligence including machine learning and deep learning algorithms. Documented programming skills in Python, R, or MATLAB. Very good knowledge of English, spoken and
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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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. Experience with basic mathematical principles and their application in modelling. Familiarity with programming languages such as Matlab or Python . Given the interdisciplinary nature of the project, a strong
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(e.g. Python, R) Experience working with Gram-positive bacteria Consideration will also be given to good collaborative skills, drive and independence, and how the applicant, through his or her experience
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one or more of the following areas: Single-cell and spatial transcriptomic methods Scientific programming in Python and/or R Machine learning or deep learning frameworks (e.g., PyTorch, TensorFlow
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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