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GPU-capable, parallelized simulation frameworks. Work closely with experts in HPC and power systems to enhance scalability and computational performance. Disseminate your findings through scientific
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strong background in applied mathematics Excellent programming skills (Python, C/C++) Good experience in machine learning and parallel computing Good organisational skills and ability to work both
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imaging over multiple generations. In parallel we will build upon our new experimental and computational framework that links phenotype to function at the single-cell level (named “Look-Seq2”). Strong
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Description Thinking of doing your PhD in the Life Sciences? The International PhD Programme (IPP) Mainz is offering talented scientists the chance to work on cutting edge research projects
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edge of energy systems and computational engineering, developing scalable methods to simulate and secure IBR-dominated grids. Your key responsibilities include: Conducting large-scale simulations
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time is to be minimized by developing a robot ensemble for parallelized polishing as well as surface roughness and shape characterization. The »3D Sensors« group contributes to this goal by developing a
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Secihti call and go through a parallel application process. Please see the respective Secihti call here for further information on their selection process. The aim of the scholarship programme is to
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Analytical Food Chemistry at Technical University of Munich | Freising, Bayern | Germany | about 2 months ago
Temporary Job Status Full-time Hours Per Week 40 Offer Starting Date 1 Jul 2026 Is the job funded through the EU Research Framework Programme? Horizon Europe - MSCA Is the Job related to staff position within
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surrogates or approximators, such as random forests or shallow neural networks, trained to mimic the outputs of the original computations at a fraction of the cost. This hybridization aims not only
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related in space and time and to behavioral events. Core Tasks: Getting familiar with the experimental data and the concepts of neuronal coding, and Elephant Analysis of the parallel rate data for