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Control of Buildings (https://annex96.iea-ebc.org ). Responsibilities and qualifications The primary objective is to advance scalable modeling methodologies for building energy systems by combining physical
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with: Code maintenance and development (Python): Refactor and document code and keep the codebase maintainable and aligned with project goals. Testing: Try test cases, evaluate the performance Data
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various data analysis tasks. Your work will focus on carrying out data preprocessing, data wrangling, and carrying out analyses using R (and sometimes Python). Example projects you will be working
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, genetics and physiology Experience with bioinformatics and coding in Python or other programing language Experience with protein software tools like AlphaFold3, Boltz2, PyMOL, Chimera, etc. Interest in
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Andres Masegosa (arma@cs.aau.dk), Department of Computer Science. (please see: https://andresmasegosa.github.io/ . The project’s domain PI is Professor Jamal Jokar Arsanjani (jja@plan.aau.dk), Department
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. in R and Python) Support/manage data collection pipeline from instruments in the lab & field (including visualisation of data in e.g. Origin) Establish, maintain, and refine documentation regarding all
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Python or similar. Experience with optics and/or reflectometry for X-rays and/or neutrons. Personal drive and self-motivated. Good communication skills in English, both written and spoken. Being able
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driving our success in this exciting and quickly growing field. Where to apply Website https://cv.newton-6g.eu Requirements Research FieldComputer scienceEducation LevelMaster Degree or equivalent Research
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., in C++, Python or Matlab. Who we are The successful candidate will be hosted by the Section on AI & Sound. This section is led by Prof. Jan Østergaard. A dedicated supervisory team composed of experts
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- Knowledge in programming in Python or R - Familiarity with machine learning or deep learning methods is a plus - Interest in plant genomics, evolutionary biology, or comparative genomics - Proficient in