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Field
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the project. Strong research profile in the applications of machine learning, artificial intelligence, multi-objective optimization, spatiotemporal modeling, and processing of satellite and high-frequency flux
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with the PI and research team to interpret findings and optimize methodologies. Attend and present at scientific conferences. Knowledge – Skills – Abilities Programming experience is required. Prior
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of deterministic and stochastic dynamical systems, optimal control, network models, and machine learning. Preference will be given to candidates with experience in these areas. The researcher will work closely with
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students, interact with collaborators, and adopt and optimize relevant techniques for the project where applicable. Professional development: 5% Requirements PhD in molecular biology, cancer biology
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, biochemical assays, testing with pharmacological compounds and mouse models. The postdoc will write manuscripts, mentor students, interact with collaborators, and adopt and optimize relevant techniques
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optimizing the squeezing of the vacuum to minimize quantum noise, a prototype cryogenic interferometer, using machine learning for nonlinear feedback control, devising techniques to quell opto-mechanical
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such as PyTorch and TensorFlow. Experience with high-performance computing and/or scientific workflow. Strong background in inverse problems, numerical optimization and image processing. Job Family
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complex endometrial models and optimizing in vitro implantation assays. Culturing human embryos and generating stem cell-based embryo models. Tissue sectioning for advanced spatial transcriptomic analysis
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experience. Research background in decision making systems, in particular the use of different optimization, machine learning, and decision making modeling techniques for problem solving. Desire to grow
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with optimization techniques and accelerated computing are a plus for this position. Strong written and spoken English skills are required. The successful candidate will: (1) develop novel methodologies