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Field
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computational modeling techniques to study planning in rodents engaged in dynamic spatial foraging tasks. The successful candidate will develop computational models of reinforcement learning in the brain and
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mechanisms of fertility loss in females, the role of the microbiome in reproduction, susceptibility of hens to diseases including avian influenza, using organoid models to investigate reproductive function and
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of Nevada, Reno (UNR) invites applications for a Postdoctoral Position: Supply Chain Modeling for Water Networks and Lithium Supply Chains. We are seeking a dedicated and innovative postdoctoral researcher
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talks at national meetings Draft manuscript for publication III. Mentor for Graduate Students Serve as mentor and role model junior members of the lab. This role includes answering questions if the PI is
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: Expertise in interpreting LC-MS, GC-MS, Raman spectroscopy, and NMR data. Experience in metabolic profiling and quantification of bioactive compounds in plants. Familiarity with computational modeling
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glovebox operation. Demonstrated problem-solving and innovation skills. Organizational and critical thinking skills. Able to prioritize and manage time effectively. Ability to model Argonne’s core values of
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programming. Strong oral and written communication skills. Excellent collaboration and teamwork abilities. Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork. Preferred
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independently as well as in collaboration with a multidisciplinary team. Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork. Desired: Any prior research experience in
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engineering controls such as gloveboxes or hoods is desired, but not mandatory. Strong interpersonal, written, and oral communication skills. Ability to model Argonne’s Core Values: Impact, Safety, Respect
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with a team. Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork. Preferred Knowledge, Skills, and Experience Experience in machine learning/deep learning methods