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Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. | Dortmund, Nordrhein Westfalen | Germany | about 5 hours ago
. or Diploma in bioinformatics or a comparable qualification Extensive programming experience Practical experience in machine learning and the application of large language models Knowledge of OMICS and image
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implementation and commissioning Knowledge of machine learning or reinforcement learning applied to control systems is a strong asset Experience with accelerator technology, specifically photocathodes is an asset
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for working in a competitive interdisciplinary research team are essential. Potential scientific projects will use computational neuroscience methods such as dimensionality reduction, machine learning
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Apply online now: https://karriere.klinikum.uni-heidelberg.de/index.php?ac=application&jobad_id=29009 Data Scientist/Computational Scientist – Multimodal and Multi-Agent AI for Precision Oncology (m
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elements. By integrating machine learning, structural optimisation, and automated code-compliance verification, the platform will enable designers to create structural designs based on available reclaimed
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limited time until 31st of December 2032, available immediately Key Responsibilities: Design, implement and refine automated image analysis workflows, including machine learning–based methods
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existing technologies, right through to the tested prototype. The Data-based Methods team at Fraunhofer ENAS develops real-world applications using AI, machine learning and computer vision. The main focus is
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existing technologies, right through to the tested prototype. The Data-based Methods team at Fraunhofer ENAS develops real-world applications using AI, machine learning and computer vision. The main focus is
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and Earth Surface Geochemistry (department “Geochemistry”), we are looking for a: Reference Number 11412 Project Iso-Orbi: Using high-resolution mass spectrometry for simultaneous multi-element stable
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memory chips! By merging logic and memory elements, costs and the required wafer area can be minimized, and above all, energy efficiency and speed can be maximized. Specifically, in this project we