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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | about 2 months ago
Student (f/m/d) in Quantum Algorithms for Fluid and Environmental Flow Modelling. Your tasks # Development and implementation of numerical and algorithmic methods for the simulation of fluid-dynamical
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RAP opportunity at National Institute of Standards and Technology NIST Development of New Computational Methodologies for Molecular Simulation of Soft Materials Location Material Measurement
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atmospheric sciences • Knowledge of cloud or aerosol physics • Experience in algorithm development and satellite remote sensing • Good written and spoken English • Ability to work independently as well as in a
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The Faculty of Engineering, Department Electronics and Informatics, Research Group Electronics and Informatics: Research – Development - Innovation is looking for a PhD-student with a doctoral grant
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evolution of satellite communication systems, driven by the deployment of large Low Earth Orbit (LEO) constellations and the integration of non-terrestrial networks into future 6G infrastructures, is
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algorithmic components and primarily programming courses with a focus on bioinformatics methods. Such graduate courses seek experienced bioinformatics, biotech, and data science professionals with a desire to
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Doctoral Candidates (DC1 and DC2) to carry out research in neuromorphic photonic-electronic integrated circuits for brain-inspired information processing and sensing (DC1) and in the development of efficient
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of promising nanoagents. The objective of this doctoral project is to develop an innovative method for sensing and quantifying the hotspot effect in aqueous suspensions of optically absorbing nanoagents, without
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oversee and develop algorithms for analyzing ensemble genomics data, single cell genomics data, single cell merFISH and sequential oligopaints imaging data, as well as novel molecular connectomics data
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project team regularly use for the production of model colloidal films, ceramic dielectrics, photovoltaics and battery electrodes to provide the datasets required to educate the machine learning algorithms