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proficiency in relevant programming languages (e.g., Python, C++) and tools such as ROS. Experience in simulation and digital twins, as well as the use of synthetic data for training machine learning models, is
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that merge thermo-fluid dynamic laws, deep learning, and experimental data. A central goal is to overcome current limitations in TES operation and optimization, enabling discovery of new high-performance and
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. For information of eligibility of completed programmes, see General assessments for specific countries and Assessment database . Terms of employment Employment as PhD fellow is full time and for maximum 3 years
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. The Institute’s main purpose is to address basic scientific questions through interdisciplinary approaches. The institute operates at the intersection of natural and medical sciences and the humanities. Information
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data from large scale DTU pilots Conduct pilot-scale CO2 capture experiments up to TRL7 Perform physical-chemical analysis of innovative solvents and gases The preferred candidate should have the
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Epidemiology, your primary tasks will be to: Develop and validate novel computational tools for analyzing metagenomic data Publish peer-reviewed research articles on bioinformatic tools and their application
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The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the
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will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD
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of prior data?) Additional research topics may include: Algorithmic Transparency and Fairness in Funding Decisions Comparative Analysis of Funding Models AI-Driven Predictive Analytics for Funding Success
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21 Aug 2025 Job Information Organisation/Company University of Southern Denmark Department Department of Mathematics and Computer Science Research Field Computer science Researcher Profile First