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PhD Position in Theoretical Algorithms or Graph and Network Visualization - Promotionsstelle (m/w/d)
31.07.2025, Wissenschaftliches Personal The Chair for Efficient Algorithms, led by Prof. Stephen Kobourov, is inviting applications for a fully funded PhD position at the Technical University
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Your Job: Explore bio-inspired algorithms through simulation—both numerical and circuit-based—and experiment with existing hardware, including CMOS and memristor circuits. Additionally, will need
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inviting applications for a PhD Student (f/m/x) for the project Theory and Algorithms for Structure Determination from Single Molecule X-Ray Scattering Images Project description Single molecule X-ray
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21.12.2021, Wissenschaftliches Personal The Department of Computer Science, Technical University of Munich, has a vacancy for a PhD candidate/researcher position in the area of efficient algorithms
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starting date is November 2025. The topic of the PhD project will be theoretical research in discrete optimization, with a particular focus on either graph algorithms or multiobjective optimization
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13.01.2020, Wissenschaftliches Personal PhD position at the Chair of Algorithms and Complexity. Candidate shall work on approximation algorithms for scheduling problems in parallel and distributed
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learning (ML) methods—including surrogate modeling, feature extraction, and inverse design algorithms Generate synthetic microstructures (based on the open source OptiMic software) Perform descriptor
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proteins Dario Riccardo Valenzano - TE Landscapes in African Killifish: Evolutionary Origins, Diversification, and Activity During Aging Claudia Waskow - Mechanisms of immune aging in mice - histone
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Dortmund, we invite applications for a PhD Candidate (m/f/d): Analysis of Microscopic BIOMedical Images (AMBIOM) You will be responsible for Developing new machine learning algorithms for microscopy image
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motivation in conducting evolutionary and chemical ecological research at different levels. •MSc/diploma in a relevant field (e.g., evolutionary biology, chemical ecology, sensory biology). •Strong experience