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, and training methods - across multiple technological platforms - photonics, electronics, biological neurons. Responsibilities and tasks This PhD project aims to develop, verify, and benchmark learning
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. The methodology is focused on hybrid Physics Informed AI methods, time series, prediction, causality discovery, data analytics, advanced visualization to monitor and forecast natural and human activity in support
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using technologies such as single cell genomics to characterize mammalian autism models, as well as using molecular tools to develop a high-throughput method to study local mRNA components of synapses
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but not limited to mice, rats, rabbits, dogs, cats, sheep, pigs, cattle and nonhuman primates. Significant experience related to animal handling, methods of blood collection and drug administration
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them to optimize any results, working to obtain new tool compounds and drug candidates. Leveraging state-of-the-art computational methods, including structure-based ultra-large virtual screenings
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ecological modelling. • Interest in undertaking field work and laboratory analysis (eDNA) methods to monitor and evaluate risks of algal blooms in reservoirs. • Familiarity with computer programming
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core network while utilising a virtual template from experiments for cellular growth and division will be used. In addition, AI methods for generating regulatory hypotheses between genes, hormones and
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of the supervisor. Equipment Operated: Computer and all other standard office equipment. Work Schedule: Typically, Monday through Friday. Potential for remote work. Supervision Exercised: May exercise supervision
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eligibility, please visit: http://uhr.rutgers.edu/benefits/benefits-overview . Posting Summary Outstanding applicants are desired for a Part-Time Lecturer (PTL) teaching position as Co-Course Director for a
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needs and continued code compliance; Assists in developing and implementing building inspection and plan review routines, methods, policies, procedures, and standards; Assists in the development and