217 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in Germany
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04.04.2025, Wissenschaftliches Personal The Chair for Computer Architecture and Parallel Systems (CAPS) offers this position as part of the DARE-project funded by the EuroHPC JU bringing together
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Immunology and Computational Biology Reference number: 2025-0105 We are deploying advanced in vitro and in vivo model systems, genetic perturbations and single cell technologies with spatial readouts to study
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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | 7 days ago
compact, lightweight and robust holographic instruments Develop real-time data pipelines using edge computing, built on our existing toolchain and enhanced with machine learning tech-niques Validate
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. Requirements: Completed university degree in computer science or applied mathematics, remote sensing, geophysics, physics, or related areas Expertise in computer vision and/or machine learning (deep learning
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, computer science, mathematics, physics, or a related field with an outstanding academic record. Interest in mathematical signal processing, optimization, and/or machine learning is important. Since
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Postdoctoral Researcher (m/f/d) in Cognitive Psychology / Computational Neuroscience to be filled as soon as possible. The position is limited to 3 years and can be extended for another 3 years. Your task
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teaching and curriculum development. Your qualifications PhD in computer science, data science, applied mathematics, physics, or a related field. Strong expertise in machine learning and deep learning
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in an area of safe machine learning and/or applications in healthcare Management of a team of PhD students, postdocs, and software developers Coordination of the implementation of research prototypes
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of these patients. The goal of this project is to combine cutting-edge multi-omics technology, data analytics, machine learning and clinical samples from the human eye to decipher new insights into disease mechanisms
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or a related discipline A solid background in climate and atmospheric sciences, and extreme weather ideally supported by knowledge of machine learning and time series analysis is of advantage, as is