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the application which project you are specifically interested in. Further details on the projects can be found here: https://www.fz-juelich.de/en/jcns/careers/fellowships/tasso-springer-fellowship-program Your
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networks. The interdisciplinary approach of DYNABIO bridges biology with computer science, mathematics, chemistry, and physics. Research carried out within DYNABIO teams spans a wide range of models and
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computational skills and expertise in causal inference or network science are desired but not required. Start date and term are negotiable. Additional Qualifications Special Instructions For more information
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Doctoral (PhD) Candidate to join the new MSCA Doctoral Network FairCFD (https://www.imft.fr/faircfd/project-presentation/ ). The candidate will enrol for a PhD in Chemical Engineering at the University
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Job Description Job Alerts Link Apply now Job Title: Research Fellow in Quantum Networks Posting Start Date: 16/01/2026 About the Centre for Quantum Technologies (CQT) The Centre for Quantum
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Application Deadline 15 May 2026 - 23:59 (Europe/Madrid) Country Spain Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme
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Science Group: Telecommunications and Networking - Av Work Objectives: 1 – Analysis of the state of the art in federation mechanisms on Multi-access Edge Computing environments 2 – Analysis of advanced
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | about 3 hours ago
Applicable Offer Starting Date 9 Mar 2026 Is the job funded through the EU Research Framework Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer
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position We invite applications for position as PhD Research Fellow in Multisensory Networked Interactions with Robotics Avatars available at Department of Informatics. The fellowship period is three years
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computational chemistry, reaction network analysis, and machine learning for organometallic catalytic reactions. 2. Design of membrane-permeable macrocyclic peptide drugs via machine learning structure