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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 29 days ago
algorithms for solving partial differential equations # Implementation, testing, and benchmarking of computational methods on high-performance computing and quantum computing platforms # Analysis and
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acquisition. Finally, the candidate will perform processing and analysis of the acquired data. V - Initial grant duration: Twelve (12) months V.I - Renewal Possibility: Non-renewable VI - Funding and financial
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tasks, contributing to the analysis, interpretation, and integration of the data obtained. He will actively participate in scientific meetings, report preparation, and dissemination of results. V
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Research Unit. Selection criteria: The final classification (FC) will be awarded on a scale of 0 to 20 points, based on the CV analysis, in accordance with the following selection criteria and their
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the analysis of genomic and transcriptomic data. Preference will be given to candidates with experience in the use and development of computational tools for theanalysis of regulatory networks. Additional
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August. 2.2 – Specific Requirements: a) Academic background: Master’s degree in Life and Health Sciences, Neurobiology or related scientific field, with experience in physiology data analysis; b) Not
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based on excimers and neutral bremsstrahlung radiation, in various noble gases and molecular mixtures; d) Data analysis: signal processing and analysis of the results obtained in the previous task. Work
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candidate will carry out R&D activities within the scope of the UVineSafe project, namely: 1) Survey and analysis of existing data (Months 1–2): collection and organization of historical and current
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 29 days ago
with industrial and academic partners and to participate in experimental campaigns; a secondment of around 3 months in Cape Town, South Africa is planned # Good programming skills for data analysis
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Images Work Plan: -Review of the state of the art on image segmentation models. -Implementation of prototype optimizers for neural networks. -Experimentation with the developed prototype and analysis