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for a Kawader Research Assistant Fellow position to support the project Evolutionary Genomics of Adaptation. The goal of the project is to determine the genomics basis of adaptation to extreme
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that underpin moral judgment - rule-following, outcome evaluation, bargaining mechanisms - are themselves products of this evolutionary process, shaped to facilitate cooperation under human time, information, and
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at the Intersection of Information, Society, and Methodology (PRIISM) is seeking a part-time senior research scientist to support the Algorithms, Data, and Public Policy Technology (ADAPPT) Lab’s applied research
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goals and those of faculty mentor; and publication of research findings/scholarship during postdoc appointment period. Projects in the Rocha lab address the evolutionary history of populations and species
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and optimize advanced signal processing algorithms for joint communication and sensing. Analyze experimental datasets, extract statistical models, and compare findings across environments, hardware, and
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. The successful applicant will have the opportunity to develop an autonomous line of research related to the interests of the lab in evolutionary genomics. Motivated applicants with a strong background in
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generation initiative. Our laboratory has expertise in deep learning, including deep reinforcement learning, large language models, and the theory of deep learning. The candidate will develop DRL algorithms
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datasets Implement LLM and Machine Learning algorithm Conduct statistical analysis in SAS or Stata Assistant with other ad hoc tasks Required Education Bachelor’s or Master’s degree in computer science
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analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models Statistical
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the racial justice implications of technology and algorithmic decision-making tools in the criminal legal system and other systems that govern people’s lives; challenging the forces that drive racial