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dependent predictive deep learning models, and physical mechanistic models (thermodynamic and kinetic models etc.). Examples of suitable backgrounds: machine learning, programming, mathematics, physics. You
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related fields. Experience in Machine Learning/AI, mathematical, computational and statistical training are also advantageous. About the employment The employment is a temporary position of two years
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of the proteins involved in the project, but also applying machine learning to predict the effects of allosteric modulation and to understand the biology of the specific systems we are studying. Qualification
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registries and biobanks. The applicant is expected to have a strong computational focus on innovative development and application of novel data-driven methods relying on machine learning, artificial
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innovative development and application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. More specifically, at NRM this research will be
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spatial mass spectrometry. Experience with single-cell omics is also an advantage. Advanced biostatistics and machine learning, such as multivariate analysis, regularization, deep learning, or network
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methods relying on machine learning, artificial intelligence, or other computational techniques. Duties The position includes research, teaching and administration. Duties includes conducting research
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on machine learning, artificial intelligence, or other computational techniques. Main responsibilities Research and in addition some teaching and supervision. Qualification requirements In order to qualify
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application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. Your tasks will include conducting independent research in the subject area at
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for version control. Ability to quickly learn new skills. High proficiency in Unix/Linux environments. Excellent verbal and written English skills. Additional qualifications In addition to the qualification