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will pursue a Ph.D. degree (Doctorate) in computer science or software engineering with a focus on differential privacy (DP) and other secure computing techniques while collaborating with the Ministry
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as part of the CET (Comité d’Encadrement de Thèse) and will be daily supervised by the Postdoc employed in the project by UL. The PhD candidate will join the Mobilab Transport Research Group, a dynamic
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) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission of teaching and
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Health. METAMIC 3 is funded by the European Commission under the Horizon Europe framework programme (Grant Agreement number 101225682). The METAMIC 3 project will embed Doctoral Candidates (DCs) in a
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The Department of Finance at the University of Luxembourg invites students to apply for Doctoral researcher positions in Finance. The program follows the standard international format with rigorous
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job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Temporary contract | 14
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Application Deadline 12 Nov 2026 - 07:52 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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through the EU Research Framework Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you passionate about research? So are we! Come
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We offer a fully funded PhD student position within the TruX Research Group headed by Prof. Dr. Tegawendé F. Bissyandé. The position is supported by Google.org and is embedded in a broader research agenda on multimodal and multilingual language models. The successful candidate will focus on the...
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SD- 26053 PHD IN ULTRA-FAST MACHINE-LEARNING INTERATOMIC POTENTIALS FOR NANOINDENTATION OF TIC MA...
PhD candidate to develop and apply ultra-fast machine-learning interatomic potentials (UFPs, Xie et al., npj Comput. Mater., 2023, 10.1038/s41524-023-01092-7 ) for long, multi-million-atom molecular