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and documented background in machine learning, deep learning, data analysis and programming. Previous experience in research and knowledge in bioinformatics, biophysics, biochemistry, molecular biology
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experts in the field of protein engineering, protein production, affinity ligand design and characterization, and machine learning for protein design. This unique PhD position is a 4-year collaborative
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advanced biostatistics/machine learning analyses, but also with other types of analysis. The work involves supporting Swedish researchers under a “user fee-based” support model. The projects will differ in
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and/or functional imaging or application of computational modeling, machine learning and AI to understand cellular function. At least five years’ experience working within the university system, another
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in transition is key. We also take pride in delivering education to enable regions to expand quickly and sustainably. In fact, the future is made here. Are you interested in learning more? Read about
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in transition is key. We also take pride in delivering education to enable regions to expand quickly and sustainably. In fact, the future is made here. Are you interested in learning more? Read about
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Sciences division. This multidisciplinary team utilises a combination of machine learning and mechanistic modelling to derive models and scientific insights from data, which both support and enhance drug
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on applying AI and machine learning to molecular design challenges. This position is one of several industrial PhD roles funded by the DDLS program, which supports training in four strategic areas: cell and
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evolutionary analysis. A central component of the research will be to develop machine learning and deep learning methods trained on coding sequences and protein structure to extract patterns in data and to draw
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of small cryptic plasmids in the development and spread of antibiotic resistance, and ii) Use machine learning tools to examine the complex interplay between bacterial hosts, various plasmids and resistance