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interdisciplinary professional partners. • Other duties as assigned. Requirements: • PhD degree in computer science, applied mathematics or electrical engineering, with a focus on computer vision/machine learning
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on and defensive mechanisms for safe multi-agent systems, powered by LLM and VLM models. Candidates should possess a PhD (or be near completion) in Machine Learning or a highly related discispline. You
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Student Shops (PSSS) and provide advanced CNC fabrication support in the KSAS Physical Sciences Machine Shop (PSMS). This role multi-fold and involves a) managing multiple fabrication spaces, providing
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to the advancement of AI applications in biological sciences. This role presents a unique opportunity to work with pangenomic datasets while exploring the application of Large Language Models (LLMs) and machine
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spatial omics datasets. The position will also contribute to multi-modal data integration efforts that combine imaging, genomics, and machine learning approaches. Key Responsibilities Data Processing
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2025. Encouraged by the continuing success of modern machine learning (ML) techniques, researchers have become ambitious to develop ML solutions for challenging science and engineering problems with
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workstreams, and the PhD’s will be working along senior staff to perform tasks in different workstreams, in strong collaboration with multiple international partners and fellow PhDs from all over the world. Key
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health records (EHR), waveforms from bedside monitors, radiology images and wearable sensors. This position offers a unique opportunity to work closely with clinicians on applications of machine learning
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of this project will bring forward the integration of novel methods at the intersection of advanced control, optimization, manufacturing science, robotics, and machine learning. The doctoral student position we
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tools. In this role, you will mainly focus on strengthening our computational pipeline: integrating multiple standalone machine‑learning predictors into a unified, multi‑objective framework capable