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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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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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northern Europe. Our research covers a broad spectrum of fields, from core to applied computer sciences. Its vast scope also benefits our undergraduate and graduate programmes, and we now teach courses in
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master degree degree is required in relevant areas such as remote sensing, computer sciences, and mathematics. You are also required to have strong background in deep learning for image analysis, e.g
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, so you should be motivated to work in the lab, eager to learn new techniques, and able to take initiative. You should also be organized and capable of working independently as well as collaboratively
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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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Applications: Applying machine learning or AI to predict gene function or discover functional relationships from perturbation data. Familiarity with proteomics-specific public repositories (e.g., PRIDE) and
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Chemistry (experimental/computational physical chemistry) -Transition metal photocatalysts studied by femtosecond X-ray science with a focus on hybrid experimental/machine-learned structural dynamic analyses
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between KTH Mathematics and Nordita under the Wallenberg Initiative for Networks and Quantum (WINQ), offering a stimulating environment at the interface of mathematical statistics, machine learning, and the
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well as digital filters is advantageous. Your workplace You will be working at the Division of Electronics and Computer Engineering (ELDA), which conducts teaching and research in a broad range of areas, from