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Field
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networks, from a machine learning and information theory perspective. This basic research project has strong translational potential and aims to elucidate how immune function is altered during sepsis, with
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regulation to address the challenges of trust, compliance, and usability in next-generation networks. The inTRUSTED Living Lab will foster collaboration between researchers, industry and policymakers, ensuring
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methods (e.g., variational autoencoders) applied to biomolecular dynamics data. ● Familiarity with elastic network modeling (ANM/GNM) or the ProDy software package. ● A track record of independent
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of Transition Edge Sensor (TES) bolometers for studies of the Cosmic Microwave Background (CMB), while also supporting the exploration of novel applications for superconducting detectors. As a member of Argonne’s
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deposition infrastructure Opportunities for professional growth and networking Competitive salary and benefits package The contract duration is initially for two years with the possibility of extension and a
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. This position is designed for scientists with strong computational and quantitative training who are interested in agent-based modeling, network science, infectious disease dynamics, uncertainty quantification
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-sequencing datasets from across a large, international collaborative research network. The role involves establishing a robust pipeline to generate a transcriptome-wide map of STR expression in PD brain tissue
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establish a sustainable line of cooperation between UHK and leading European groups and networks in cosmology and gravitational-wave physics. Depending on mutual scientific interests and appropriate
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post holder will work on an MND Association-funded project to map the interaction network of Annexin A11 and elucidate its role in neurodegeneration. The research aims to uncover how protein–RNA and
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the holistic understanding of space and its broader societal, ethical, and environmental impacts. Through responsible, multi-disciplinary research, including novel sensors, environment modelling