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Field
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multidisciplinary team comprised of fellow postdoctoral appointees, experimentalists, and staff scientists, with computational fluid dynamics (CFD) and artificial intelligence/machine learning (AI/ML) expertise, with
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
association with NOAA's Geophysical Fluid Dynamics Laboratory (GFDL), seeks a postdoctoral or more senior research scientist to develop hybrid models for sea ice that combine coupled climate models and machine
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engineering and nuclear-chemical engineering systems Create new reduced-order models and submodels related to the fluid flow, heat transfer, thermochemistry, and electrochemistry in multiphase systems Use
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, lipid vesicles, polymer physics, active materials, single molecule biophysics, biomaterials, materials chemistry, fluid mechanics, rheology, and computational modeling. Candidates should apply at https
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researcher should have expertise in materials/mechanical/electrical engineering with an excellent understanding of fluid mechanics as well as experience with Arduino/Raspberry Pi programming, 3D printing and
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independently perform surgery and perfusions on experimental animals. • Collect tissue and fluid samples (e.g., body fat, brain tissue, blood) from experimental animals; store and analyze the tissue (e.g., ESLISA
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Hands-on experience and a strong understanding of metabolomics/dereplication of natural products by LC-MS/MS (preferably by molecular networks) Solid experience in purification of natural products (by
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projects of the research group Qualification Required: A diploma and a PhD in microbial natural product chemistry Hands-on experience and a strong understanding of metabolomics/dereplication of natural
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of molecular reactions occurring at the surface of various materials. In addition, computational fluid dynamics (CFD) simulations combined with microkinetic modeling will be carried out to study the heat
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demonstrator sites where crushed basalt is being applied. The PDRA will use pH stat experiments with calcite seeds to assess the threshold of elevated alkalinity at which calcite precipitation occurs in filtered