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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 1 month ago
, environmental engineering/science, computer science, industrial or mechanical engineering, and decision science. The successful candidate will contribute to ongoing NSF-funded research projects during the initial
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The successful candidate should have: Master’s degree in Industrial Engineering and Management, Mechanical Engineering, Energy Systems, Control Engineering, Data Science, or a related field, with solid foundations
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computational modelling to be used to design and re-engineer flower architecture. The RA's main focus will be on computational modelling of gene regulatory networks for predicting the mechanisms leading
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PhD Studentship: Dissecting the Molecular Architecture and Function of LMTK3 as a Therapeutic Target
; University of Sussex | The City of Brighton and Hove, England | United Kingdom | about 1 month agomechanisms underpinning LMTK3's multifaceted role in cancer biology. By employing a multidisciplinary approach combining structural biology, biochemistry, and cell biology, this research aims to provide novel
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Cranfield University's tailored researcher training programme – setting you up for a rewarding career in water science and environmental technology. Per- and polyfluoroalkyl substances (PFAS), also known as
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understanding of the mechanisms of initiation, progression, and therapeutic resistance in lung cancer. The lab has established the use of multiple high-throughput screening technologies, genomics, proteomics
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state of Rhineland-Palatinate. Our research focuses on the biology of the cell nucleus and ranges from the molecular level to systems and computational approaches. Researchers at IMB are supported by
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Apply online now: https://karriere.klinikum.uni-heidelberg.de/index.php?ac=application&jobad_id=25655 PhD Student – Bioinformatics/ Computational Biology (m/f/d) Stellenanzeige merken Stellenanzeige
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paramount. Secure and trustworthy AI-electronics focus on embedding security features directly into hardware, such as hardware security primitives and tamper detection mechanisms. This field addresses
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inductive biases, we aim to identify key mechanisms that drive rapid learning in the visual system. The goal is to create a robust mechanistic neural network model of the visual system that not only mimics