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(SHORES) and the Division of Engineering, New York University Abu Dhabi, seek to recruit a Postdoctoral Associate to work on a fascinating project focused on the development machine-learning powered digital
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for candidates to have the following skills and experience: Essential criteria PhD qualified in mathematical, physical or computational sciences Experience in using machine learning methods to analyse datasets
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approaches and will integrate novel hardware (including electrode arrays, microdevices, analytical systems) into automated robotic pipelines You will also apply machine learning-based analyses to imaging and
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experience with machine learning frameworks such as PyTorch or scikit-learn. You are a team player and a team leader: you can mentor PhD students and Bachelor students effectively. You share your knowledge
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patent filings. The work will be centred around topics such as machine learning for communications, communication theory, signal processing for communications, coding theory, and information theory. Your
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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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-$60,000 Type of Position Student Position Time Status Full-Time Required Education PhD Required Related Experience N/A Required License/Registration/Certification N/A Physical Requirements Check all
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comes with no teaching obligations BASIC RESPONSIBILITIES AND OBLIGATIONS Conducting research related to the scientific project titled “Calculus of variations in machine learning problems”, in particular
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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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reinforcement learning and other approaches for cross-domain generalization Qualifications Essential: PhD in Computer Science, Machine Learning, Computer Vision, Natural Language Processing, or closely related