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to optimize utility of captured signals Conceive, write, and submit proposals to develop and expand a research program investigating signal collection and analysis for mission objectives Qualifications: A PhD
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full benefits. Key Responsibilities: Developing and adapting protocols and techniques for lead detection in field and laboratory settings - including the analysis of consumer products like spices, paint
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mechanisms involved in the physical mechanisms of cellular self-organization during early mouse embryo. Develop new machine learning models to learn minimal dynamic models of gene regulation from longitudinal
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Researcher (R2) Positions PhD Positions Application Deadline 24 Apr 2026 - 23:23 (Europe/Lisbon) Country Portugal Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 6 Apr
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, PhD, and undergraduate students. Excellent communication skills, time management, and self-motivation will be essential for this role. For enquiries about this position please contact Professors Richard
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into the core of manufacturing workflows, dynamically adapting to shifting conditions with enhanced human decision making. FLARE's mission is to create an adaptive, self-optimising manufacturing ecosystem where
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how the adaptive immune system recognises and responds to foreign and self-antigens. The successful candidate will employ a broad suite of immunological and molecular tools—such as flow cytometry, cell
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timely manner Maintain strong commitment to the implementation and perpetuation of ORNL core values and ethics Basic Qualifications: A PhD related to computational or theoretical physics, chemistry
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an adaptive, self-optimising manufacturing ecosystem where production lines can reconfigure in real-time, in collaboration with domain experts (e.g. operators, planners, designers) that are supported by digital
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privacy-preserving and decentralized online learning methods deployed in converters/drives so that fleets of motor applications (e.g., pumps, fans, compressors) can self-quantify and aggregate flexibility