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: Doctoral degree (PhD) in physics or a MSc in mathematics, computational science or engineering Strong background in HPC and scientific computing and strong interest in numerical algorithms and
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further academic qualification. Professional assignment: Chair of Scalable Software Architectures for Data Analytics (Prof. Dr. Michael Färber) Research areas: Natural Language Processing, Large Language
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PhD position / Postdoc position (all genders) in AI for biomedical data analysis Full time/ Part time | Temporary | Hamburg-Eppendorf UKE_Zentrum für Molekulare Neurobiologie (ZMNH) Better together
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Museum fuer Naturkunde, Leibniz Institute for Evolution and Biodiversity Science | Berlin, Berlin | Germany | 3 days ago
), DE PhD Awarding institution: Humboldt-University Berlin (HUBER), DE Primary Supervisor: Prof. Dr. Carsten Lueter Project duration: 18 months initial contract; the position is offered as part of a
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deployment Collaborate with interdisciplinary partners and optionally contribute to teaching and supervision Your profile: PhD or strong Master’s degree in computer science, data science, software engineering
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that mimic the ecological functions of natural deadwood. The project is conducted jointly between TUM and the Technion in Israel (Professorships of Architecture & Landscape Architecture). The advertised PhD
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position in the area of machine learning and computer simulations. The focus of the PhD project will lie on developing machine learning models for clustering, classification, regression and reinforcement
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learning and computer simulations. The focus of the PhD project will lie on developing machine learning models for clustering, classification, regression and reinforcement tasks to work with, enhance
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The Quantitative Genetics research group is interested in developing statistical genomics toolboxes to decipher the genetic architecture of important crop traits, such as grain yield, adaptation
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particular, we aim to develop a neural network architecture that will allow us to accelerate solving AC power flow (AC‑PF) computations, potentially facilitating real‑time contingency analysis, rapid design