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candidates with expertise in one or more of the following specialized areas: Machine Learning / Deep Learning Uncertainty Quantification Wind Farm Flow Modelling Wind Farm Control Wind Farm Design Wind Farm
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enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education
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Job Description Join the Multi-omics Network Analytics Research Team as a Postdoc in Computational Biology at the Danish Technical University (DTU) Are you an experienced scientist with a passion
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will benefit from Lonza’s expertise and technology within peptide T cell immunogenicity, and the vast expertise within immunoinformatics and machine learning models at DTU to address this challenge
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interaction, social networks, fairness, and data ethics. Our research is rooted in basic research and centres on mathematical models of the physical and virtual world, as a basis for the analysis, design, and
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use your skills to answer fundamental biological questions in health and disease. The successful candidate is expected to leverage their skills in proteomics and computational analysis to interrogate
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. The position is part of DTU’s Tenure Track program. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial
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, laboratory testing and data augmentation. Your main goal will be to develop predictive models for assessing the degradability of bioplastics, facilitating a transition to more sustainable materials. More
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modelling approaches will also be used to complement the experimental work. The bioprocess engineering team at DTU Chemical Engineering consists of around 10 scientists and engineers. Expertise is available
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machine learning, computational modelling, and advanced data analytics can accelerate not only the discovery, characterization, and optimization of materials but also project assessment and communication