124 data-"https:"-"https:"-"https:"-"LaTIM---Brest" Postdoctoral positions in Denmark
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community, and highly livable with a green-banked meandering river cutting through the center, and attractive residential areas. For further information about the position, please contact the Head of Digital
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position, you are more than welcome to contact us. You will find contact persons at the bottom of the jobpost. Further information Read more about our recruitment process here The appointment process at
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chains, safeguard data integrity and confidentiality, and support compliance with emerging regulations, thereby meeting the rising demand for certified, secure AM solutions. What we expect We seek
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. The Postdoc will conduct research on methods to enhance the performance, safety, and lifetime of lithium-ion batteries by integrating physics-based modeling with data-driven approaches. The work will include
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Postdoc Position in Models of Quantum Programming Languages (Sapere Aude: DFF-Research Leader Pro...
computer science and mathematics, a BSc in artificial intelligence, an MSc degree in data science, and an MSc in quantum computing. Candidate Profile We are looking for highly motivated candidates interested in
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January 2026 or as soon as possible thereafter. The position is a full-time position. You can read more about career paths at DTU here . Further information Further information may be obtained from Senior
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Professor Kjeld Pedersen: kp@mp.aau.dk, phone +4599409220. Further information Read more about our recruitment process here The appointment process at Aalborg University involves a shortlisting process. You
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programming skills in Python are essential, along with the ability to design experiments, analyze results, and interpret findings. Knowledge of optimization techniques, statistical modeling, and data management
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stronginterest and experience with GIS data and tools for urban mobility with someprogrammingskills of Python/R, JavaScript, database management environments, Geographical AI and machine learning workflows
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to vastly improve our ability to recover microbial genomes from metagenomes. Specifically, we aim to take advantage of the vast amount of high-quality long-read data that is readily obtainable using