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learning methodologies. The underlying data are complex and will require sophisticated data management and integration skills. A candidate should have proficiency with GIS software and Python, strong written
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appreciated Ability to engage with interdisciplinary teams involving statisticians, computer scientists, and climate experts Programming experience in a scientific computing language (e.g., Python, Fortran
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downconversion layer Analysis of data using software tools such as MATLAB, Python, or Origin. The candidate must be familiar with materials studio software and any other materials modeling software. Experience in
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programming language (preferable: MATLAB or Python) Experience with one or several of the listed human neuroscience techniques. Ability to work and learn independently and perform research with a high level of
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, digital twins, or related areas Excellent publication record in high-quality journals and/or conference proceedings Excellent programming skills, particularly in Python and/or C/C++; hands-on experience
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data science tools, especially Python or R Proven ability to work collaboratively in interdisciplinary and international research settings Strong skills in scientific project management Excellent written
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omics (preferably related to neurodegeneration) studies is expected. Preferred Qualifications: Skilled in at least one programming language (R, Python or Perl) and experience working in Linux and/or high
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, experimental, or computational techniques. Experience in applying for research funding. Skilled in analyzing and interpreting data (e.g., using MATLAB, R, Python). Ability to write papers and reports for peer
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/ NiFi/ Knime, Programming in Python and SQL. Experience with version control systems (Git, CI/CD); Java/Scala is a plus. Familiarity with containerisation and orchestration like Docker and Kubernetes
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coding experience with e.g. Python/Matlab/R Practical experience with High Performance Computing, and scientific programming and a willingness to learn to work with high-performing computing systems