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Field
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seeking a postdoctoral researcher with expertise in data management, workflow management, High Performance Computing (HPC), machine learning and Artificial Intelligence to enhance our capabilities in making
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of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI implementation. Ability to apply AI to interdisciplinary research or developing AI models
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by candidates within five years of receiving their PhD. In particular for this position, the following is required: PhD in data science, AI, computer science, machine learning, aerospace engineering
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of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI implementation. Ability to apply AI to interdisciplinary research or developing AI models
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monitoring in manufacturing environment Develop modular, extensible workflows for data processing Develop and deploy data analytics, machine learning, and statistical modeling methods for multimodal
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, including vision, LiDAR, inertial measurements, and radio signals, to maintain coherent spatial awareness and act reliably under uncertainty. A particular focus will be placed on learning and decision-making
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collaborators. Requirements: Applicants should have a PhD in Computer Engineering, Computer Science, or a related field. Extensive and sound knowledge of ML, AI, DNN, LLMs/VLMs, Multimodal LLMs, RAG, Agentic
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for cardiometabolic disease with associated neurodegenerative conditions. It aims to develop novel deep learning algorithms, audio and vision transformers, and hybrid attention mechanisms, to detect
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required to meet the eligibility criteria. Of secondary importance are: Experience with Python and relevant libraries for machine learning, optimization and simulation. Documented expertise in simulation
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Max Planck Institute of Molecular Cell Biology and Genetics, Dresden | Dresden, Sachsen | Germany | 3 months ago
. Experience in machine learning algorithms and tools. Experience in microscopy and image analysis. Effective collaboration in interdisciplinary teams. Strong analytical reasoning and persistence in experimental