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Field
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of the Norwegian grading scale. Solid programming skills, preferably in Python. Hands-on experience in database programming. Experience in installing, training, and using large foundation/language models. Personal
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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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; Solid background in Computer Science and Mathematics; Good programming skills in e.g., Python, C, C++; Experience with Cryptography; Experience with Machine Learning is a plus; Excellent written and oral
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one or more of the following areas: Advanced computational design with Grasshopper. Programming (e.g. Python, C#). Robotic fabrication, digital manufacturing and 3D printing with sustainable materials
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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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monitoring. Familiarity with tools such as Python, MATLAB, or embedded C would be advantageous. Most importantly, this project is ideal for applicants who are motivated to tackle real-world reliability
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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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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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performance are expected. Required qualifications: Proficiency in programming (primarily Python or MATLAB) Strong communication and collaboration skills, including the ability to work across research groups and