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for users of the infrastructure. We envision that you will start with the easiest assignments and then as you learn and become more experienced, progress to increasingly difficult/qualified work
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highly recognized research. More information about us, please visit: The Department of Biochemistry and Biophysics . Project description The successful candidate will develop machine learning (ML
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education teaching and learning, or equivalent acquired knowledge, is required. A person appointed as a Lecturer but lacking training in higher education teaching and learning will be offered in-house
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solid experience in coding with R, analysis of metabolomics and proteomics data, as well as in machine learning. You also need to have good knowledge of magnetic resonance spectroscopy and multiple
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on the hypothesis that the future of building design lies at the intersection of physically sound building simulation models and machine learning (ML) techniques. Key considerations include effectively integrating ML
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organisations, military service, or similar circumstances, as well as clinical practice or other forms of appointment/assignment relevant to the subject area. Postdoctoral fellows who are to teach or supervise
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service or service/assignment relevant to the subject area. Assesment Criteria Requirements: PhD in bioinformatics, biostatistics, computational biology, data science, machine learning, molecular biology
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at the single-cell level, using tools from optimal transport, mathematical optimization, and machine learning. In addition to method development, the work includes applying and benchmarking algorithms on both
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interdisciplinary project. The project concerns algorithm design, implementations of algorithms, and simulated and biological data analysis. The student is expected to learn a bit of relevant molecular biology to
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particularly valuable. Documented experience with machine learning and biostatistics is also highly meritorious.You can find information about education at postgraduate level, eligibility requirements and