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Field
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to make decisions, solve problems, and learn. Moving from rule-based systems to agents with strategic flexibility. The range and complexity of tactics, techniques, and procedures that are supported, as
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specific drug resistance and pathogenesis mutations. The project will combine classical microbial genomics with machine learning and AI analysis approaches to create the most in depth population analysis
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• Experience in programming and deep learning frameworks • A creative mindset and curiosity to research and develop new solutions with highly skilled colleagues • Strong interest in XAI • Willingness
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The DFG-funded Research Training Group (GRK 2717) „Dynamics of Controlled Atomic and Molecular Systems (DynCAM)“ at the University of Freiburg in collaboration with the University of British
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15 full-time researchers offers a stimulating and supportive environment to learn and grow. Your profile Required qualifications: Undergraduate degree in Engineering, Physics or Mathematics with strong
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, we expect you to learn Dutch. Of course we will support you with this. Openness, supportive and flexibility are core characteristics of the team. As research scientist you will collaborate with other
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of measles evolution and naming systems (nomenclature) to support public health identification of measles outbreaks/importation and ultimately, elimination. In this project you will learn to perform genomic
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highly automated, networked mobility, featuring international collaboration with mentors from the USA, Asia, and Europe. TUD and the RTG embody a university culture that is characterized by cosmopolitanism
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accepted. The following experience will strengthen your application: Familiarity with Federated Learning We value a collaborative attitude and an interest in working both in teams and independently. Self
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, an extensive training programme in respect of industry-specific skills, and access to hotfire facilities at Westcott, Machrihanish, and elsewhere. You can learn more about the programme at r2t2.org.uk. Kick