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Supervised/unsupervised fine tuning of the existing models (e.g., Retrieval-Augmented Generation, Low-Rank Adaptation, Direct Preference Optimization, Reinforcement Learning from Human/AI Feedback). Moreover
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Profile Recognised Researcher (R2) Positions Postdoc Positions Country Poland Application Deadline 26 Sep 2025 - 23:59 (Europe/Warsaw) Type of Contract Temporary Job Status Full-time Hours Per Week 40 Offer
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will contribute to developing management and real-time operation tools to coordinate and optimize charging with PV production, while also enabling grid services. The study is further linked to two
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Postdocs, assistant professors, junior research group leaders Vocational training at the University of Tübingen International researchers Excellent research conditions Values Career development Benefits
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with PV generation. The research will contribute to developing management and real-time operation tools to coordinate and optimize charging with PV production, while also enabling grid services
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | 2 months ago
arithmetic cores for FPGAs). The team hosts 6 faculty, 6 PhD students, 3 postdocs, 2 engineer, and multiple research interns. Additional information can be found on team website: https://team.inria.fr/emeraude
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including faculty members, postdocs and PhDs working on diverse topics in the field of dynamical systems and control and its applications. This PhD position is jointly supervised by Nathan van de Wouw, Tom
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. Annual reports guarantee an optimal supervision of the progress of the projects. Scientific retreats, international meetings, exchange programmes, and journal clubs will complete the programme by giving
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topologies tailored for DC-powered HVAC units Synthesis and implementation of control strategies enabling droop-based HVAC operation with optimized energy efficiency Implementation of simulation models (PLECS
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to the timing of events and the results from performance optimization need to be included in the models. This PhD position will address these challenges by developing new timing-aware distributed supervisory