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of graph algorithms, with possible focus areas including parameterized algorithms, structural graph theory, graph symmetries and similarities, and algorithmic model theory. Tasks: scientific research
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focus on physical and mathematical aspects is required. In addition, scientific programming skills (preferably in Python) and experience with numerical models are essential. Desirable qualifications
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resolution across large genomic datasets. We focus on cancer models (osteosarcoma, breast cancer, leukemia) and on neural progenitor cells to understand how genome instability contributes to tumor initiation
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Your Job: Modeling and characterization at molecular level of selected biological processes by performing classical molecular dynamics, and employing enhanced sampling methods and machine learning
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to development of sustainable and biomedical materials. The results will be combined with theoretical modeling and simulations. Your profile Completed studies or about to be completed studies (M.Sc
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contribute to development of sustainable and biomedical materials. The results will be combined with theoretical modeling and simulations. Your profile Completed studies or about to be completed studies (M.Sc
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Karlsruher Institut für Technologie (KIT) | Karlsruhe, Baden W rttemberg | Germany | about 1 month ago
description: The focus of the RTG is on the development, characterization and modelling of novel, multi-phase composite systems capable of withstanding temperatures substantially beyond 1300 °C and harsh
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10 Oct 2025 Job Information Organisation/Company CISPA Helmholtz Center for Information Security Research Field Computer science Mathematics Researcher Profile First Stage Researcher (R1) Positions
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
produced by PBF-LB. After identification of the most relevant parameters adopting a design of experiments strategy, a probabilistic (e.g. Gaussian Process Regression) model to describe the relationship
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resolution across large genomic datasets. We focus on cancer models (osteosarcoma, breast cancer, leukemia) and on neural progenitor cells to understand how genome instability contributes to tumor initiation