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. This position is to be filled at the Institute of Climate and Energy Systems - Energy Systems Engineering (ICE-1), where we develop models and algorithms for the simulation and optimization of future energy
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in cancers of unknown primary (CUP). Your Role You will join Subproject 3 (Model Alignment and Optimization), led by PD Dr. Keno Bressem (https://scholar.google.com/citations?user=wIEgwbkAAAAJ&hl=en
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in mathematical systems and control theory, and optimization to apply for the PhD position within the Dynamics and Control section at the Department of Mechanical Engineering, Eindhoven University
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used as the groundwork by other teams at the Centre, including theory, characterization and application teams. Where to apply Website https://skk.erecruiter.pl//Offer.aspx?oid=4772058&cfg
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22 Jan 2026 Job Information Organisation/Company Chalmers University of Technology Research Field Mathematics » Applied mathematics Mathematics » Computational mathematics Researcher Profile
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implemented globally. The research includes optimization of the electrochemical processes for mercury removal as well as safe and efficient retrieval of the removed mercury and regeneration of electrodes
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will play a key role in developing and optimizing clinical quality metrics. They will also construct and maintain sustainable informatics infrastructure, as well as design integrated reporting solutions
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out and participate in the research of infrastructure and technology systems for mathematical/computational modeling and control theory for life-cycle management optimization and policy of smart and
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 30 days ago
, and innovation centre active in the fields of High-Performance Computing (HPC), Data Analytics (HPDA), Quantum Computing (QC), Artificial Intelligence (AI) and their applications. For more, see https
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for Artificial Intelligence. The position aims to strengthen methodological and algorithmic work on one or more of the following axes: Optimization and learning on very large models and datasets, improving