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Identities, Machine Learning/AI, and IoT/5G on organisations from both the private and public sectors. The group consists of doctoral and post-doctoral researchers from diverse backgrounds united in pursuit
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information about the role, please contact Prof. Radu State Your profile Strong background in AI, machine learning, or multi-agent systems, ideally with interest in financial systems, decentralized ledgers
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dynamics, data science, and machine learning are beneficial. What we offer: We offer a position with a competitive salary in one of Germany’s most attractive research environments. TUD is one of eleven
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the controlled flow at tunable temperature and photopolymerization of the precursor. The practical work will be complemented by fluid mechanics computer simulations, including solutions employing machine learning
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Environmental behaviour o Spatial analysis applied to territorial/regional planning Technical and soft skills · Basic computer skills (Word, Excel etc.) · Proficiency in statistical analysis
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of Unix systems (GNU Linux) and keen to gain hands-on experience in Networks and systems Machine Learning knowledge is a plus Strong analytical and programming skills are required (Python, Matlab, Golang
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the first call lasts from the 1st of July to 31st of August 2025. Description of specific PhD projects: Machine Learning Interatomic Potentials for Chemical Reactions Hosting: Tallinn University of Technology
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Information Systems engineering. The group conducts research on the application and the impact of digital technologies like DLT/Blockchain, Digital Identities, and Machine Learning/AI 5G on organisations from
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problems in biology by combining machine learning with in-depth knowledge of biological processes. Who we are looking for You have a Master in Science (Bioengineering, Biochemistry-Biotechnology, Biomedical
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Bioinformatics, Computational Biology, Computer Science, Biomedical Engineering, Computer Engineering, Genetics/Genomics or related field experience with ‘omics platform output experience with biological datasets