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), Agricultural Research Service (ARS), located in Hilo, Hawaii. The Agricultural Research Service (ARS) is the U.S. Department of Agriculture's chief scientific in-house research agency with a mission to find
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and academic and/or external networking Desirable criteria Teaching in Higher Education qualification (such as fellowship or associate fellowship of the Higher Education Academy) Knowledge and/or
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POST-DOCTORAL RESEARCH FELLOW - CEVIPOL (Centre de la vie politique) – Université Libre de Bruxelles
activities. Context of the Project “Resisting Interscalar Authoritarian Networks and Coalitions” (RESISTANCE) is a newly funded Horizon Europe project (Horizon call HORIZON-CL2-2025-01-DEMOCRACY-07
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electrospinning applied to drug delivery and biomaterials Demonstrable experience in cell culture work, including cell proliferation experiments Knowledge of mass spectrometric detection as used in combination with
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to observe and decode transient signaling, long-term changes, or multimodal dynamics in cell populations in the living brain. The successful applicant will also work in a multidisciplinary and collaborative
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research activities focus on clinical epidemiology and the complications of infectious diseases. MSCA Doctoral Networks. Find out more about the Horizon Europe Marie Skłodowska-Curie Actions , the European
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the Role This role will support the development and delivery of activities within the Africa Centre of Excellence for Sustainable Cooling and Cold Chain, and the Clean Cooling Network. You will
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circulation systems can be designed and operated to achieve higher net energy yield and more sustainable long-term operation. This may include models and control strategies that can improve system performance
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learning for scientific applications, including hands-on experience with neural network architectures (e.g., CNNs, autoencoders, physics-informed or hybrid models) and modern frameworks such as PyTorch
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of methods for real-time prediction of quasi-periodic hormone profiles and the detection of early signals for disease by combining mechanistic modelling with methods from machine learning to enhance inverse