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, algorithms and programming paradigms to provide input for quantum and HPC system procurements and DOE technology roadmaps. Collaborate with theorists and experimentalists to validate hardware noise models
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algorithms that combine Reinforcement Learning techniques like Partially Observable Markov Decision Processes (POMDPs) with cognitive inference modules capable of modelling human beliefs, intentions, and goals
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algorithms suitable for multi-static and distributed geometries. Understanding the performance limits of such systems, including sensitivity to synchronisation errors, geometry, transmit time, and partial
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dynamics; Explainable AI: With a particular emphasis on mechanistic interpretability. Invent, evaluate, and publish novel algorithms, aiming for theoretical guarantees when working with structured and
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features from multiple imaging modalities (CT, MRI, PET, ultrasound); (2) design advanced AI algorithms for early-stage cancer detection with high sensitivity and specificity; (3) create user-centric AI co
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 2 months ago
. Lab Research: • AI-Driven Algorithms & Software: Develop deep leering/machine learning/statistical based algorithms to elucidate lncRNAs, fusion transcripts, RNA modifications, and circular RNAs in
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of algorithmic systems. The research will investigate how clinicians interact with automated and machine learning–based decision-support systems, with a particular focus on cognitive workload, trust, situational
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network integration for emerging low-energy opto-electronic AI systems and beyond. The challenge: Machine learning and neural networks are super-charging the complexity of problems that computer algorithms
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with Graphs led by Prof. Nils M. Kriege. Our research focuses on the development of new methods and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains from
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of the screening output. This approach selects new, efficient enzymes, but also generates unique sequencefunction datasets that will be interpreted by regression and tree-based machine learning algorithms to obtain