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Field
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biology, molecular biology including mammalian cell culture is required Documented knowledge in bioinformatics and programming (Python, R) is required Experience in LC-MS and mass spectrometry is required
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-oriented way of working A distinct advantage would be: Experience with data analysis and scientific programming (e.g. Origin, Igor Pro, Python, Matlab, Mathematica) A good command of written and spoken
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: university and, if applicable, PhD degree (e.g. Master/Diploma) in mathematics, physics, materials science or related subjects basic knowledge of computer programming (e.g. Python, Matlab and C++) excellent
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this area will also be considered. The ideal candidate should be proficient in scientific programming (e.g., Python or MATLAB) and have a genuine interest in developing and testing experimental setups
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are an advantage: femtosecond laser and diagnostics, high power lasers, ultrahigh vacuum, programming skills (Labview, Python) Ability to work closely within a team: engineers, students, postdocs and scientists, and
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experience working with cohort data or electronic health records is an asset; Interest in digital health and diabetes research; Proficiency in R and/or Python; Excellent writing and communication skills in
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statistical data evaluation, creation of scientific programme codes using common software packages (MATLAB, Python, R) Simulation skills with e.g. molecular dynamics and alpha fold Knowledge
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field. A background in organic chemistry, and/or high-throughput experimentation is desirable. Proficiency in programming languages (Python/MATLAB) commonly used in machine learning applications is
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on: Technical Expertise: Documented skills in Python, Matlab, R, and a strong working knowledge of UNIX environments. Proven familiarity with biological omics data analysis techniques is essential, along with any
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field. A background in organic chemistry, and/or high-throughput experimentation is desirable. Proficiency in programming languages (Python/MATLAB) commonly used in machine learning applications is