87 algorithm-development-"Prof"-"Prof" positions at Technical University of Munich in Germany
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computer science with very good results - Interest on topics around the area of distributed systems and data management - Basic knowledge in distributed systems and graph algorithms is desired - Hand-on experience
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with the challenges of highly technologized societies, and to train future leaders with a unique sensibility for the critical interface between science, technology and society. As one of Europe’s largest
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its rich information content, conventional analysis methods have not yet fully realized its potential. This research project aims to develop a robust AI foundation model based on modern Transformer
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background or similar. You will work together with the RAISE AGRICULTURE and TUM Precision Agriculture Lab to develop an agricultural drone servicing system. You will be awarded the EXIST Start-up Grant
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RAICAM aims to train a cohort of 10 PhD students to work on the next generation of mobile robots for inspection and maintenance of industrial facilities. RAICAM will develop a multi-domain, multi-agent
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plays a key role in advancing methodological development in neutron imaging in general. We are looking for a full-time scientist (40 hours / week) to head the group as Group Leader Neutron Imaging (m/f/d
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scientific significance and public health relevance. The specific objectives of the project will be developed in relation to the candidate’s experience and interests but has a strong cell biology
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/Materials Science funded by ERC StG with excellent opportunities for both research and career development. About us Our research focuses on extracting and isolating bio-based polymers such as cellulose and
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Center TranslaTUM, which integrate bioengineering with metabolic disorders and oncology, respectively. IBMI scientists develop next-generation imaging and sensing methods to measure previously inaccessible
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/ simplified equations are used to describe LPC in different sectors. There is a strong need to advance our understanding of the LPC process and develop reliable physics-informed tools to predict and reverse