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the outcomes of SCC surgery. Job Responsibilities: As a PhD candidate, you'll focus on: Develop cutting-edge AI models: Train state-of-the-art deep learning models to segment SCC and healthy tissues using both
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to systematically understand cancer biology, identify diagnostic and prognostic biomarkers, and improve cancer therapy. Projects will involve the development of AI solutions, including machine learning, deep learning
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, working closely with AI specialists and data scientists. Methodologically, you will explore advanced deep learning approaches, including convolutional and transformer-based architectures, as well as methods
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Internal Number: 6568986 Postdoc Scholar - Marine ecology ESPM The Coastal Climate Resilience Lab - MCECO - ESPM Ecosystem Sciences Div - Carlson Lab Position overview Salary range: The UC academic salary
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methods for image classification including machine learning and deep learning. You will develop clear workflows that allow for regular update of the derived models and maps. Furthermore, you will work
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experience: Deep Reinforcement Learning, DNNs/CNNs Federated and Decentralized Learning (Split Learning, Swarm Learning, peer-to-peer FL) Fine-tuning FMs/LLMs for domain-specific applications Generative AI
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transcriptomics data analysis. Experience in quantitative image analysis, computer vision, or digital pathology. A strong background in cancer biology or immunology. Experience with machine learning, deep learning
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deep learning / computer vision / biomedical image computing Excellent English; German is an advantage for clinical collaboration We offer Highly interdisciplinary, translational research environment
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deep learning frameworks (e.g., PyTorch, TensorFlow, and JAX). • Experience in PDE/ODE modeling and numerical methods. • Strong interest in interpretable ML and mechanistic model discovery. Submit a
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. You'll be part of the Tactile Machines Lab, which is a dynamic, interdisciplinary group of researcher bringing together expertise in robotics, sensing, machine learning, biomechanics, and haptics