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Exemplify a commitment to excellence in research, operations, and community engagement, and work cooperatively to leverage scientific capabilities across ORNL. Work in a highly collaborative environment with data scientists, machine learning scientists, remote sensing scientists, HPC engineers, and geographers to deliver research and development prototypes.
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Essential Functions Numerical simulations and/or numerical modelingExperimental data analysisCoding (Matlab and/or Python and/or Fortran)Presenting research resultsWriting manuscripts Education & Experience Education: PhD Previous Experience Desired: Ocean acoustics and/or acoustical signal processing and/or ocean numerical modeling and/or inverse methods and/or machine learning.
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The Applied Mathematics and Plasma Physics (T-5) group within T-Division conducts research in novel algorithms and numerical methods for a variety of applications including fusion science, space plasma science, astrophysics, numerical analysis, machine learning, computational imaging, optimization, artificial intelligence, environmental sciences, and the modeling of critical infrastructure (gas pipelines and electrical grids.
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In Applied Mathematics, Machine Learning, Computational Biology or Computer Science with emphasis on applications in molecular biology and/or computational pathology (required). Overview :Carry out research in the field of artificial intelligence applied to computational oncology.
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Argonne’s Leadership Computing Facility (ALCF) and Mathematics and Computer Science Division (MCS) is looking for a Postdoctoral appointee working at the intersection of scientific machine learning SciML and large-scale simulation codes.
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The Center for Ionomer-based Water Electrolysis (CIWE), an Energy Earthshot Research Center, has an immediate opening for a postdoctoral researcher to conduct applied research in the area of machine learning, pattern/feature detection, statistical description, computer vision, image processing and analysis, and parallel computing.
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Research experience in machine learning, representation learning, optimization, statistics, applied mathematics, or data science. Meta is seeking a Postdoctoral Researcher to join Fundamental AI Research (FAIR), a research organization focused on making significant progress in AI. Individuals in this role are expected to be recognized experts in identified research areas such as speech, multimodality, artificial intelligence and machine learning.
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Experience conducting machine learning and inverse design models HPC experience. You will contribute to the department by conducting computational research applying CALPHAD-based ICME techniques in combination with machine learning techniques to study the mechanical behavior of alloys in extreme environments.
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Experience building systems based on machine learning and/or deep learning methods. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
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Projects may include all of the above found in the summary, including generation of dosimetric analyses, machine learning with or without integration of ontologies, toxicity assessment, ontology development, clinical data review, and/or dental science components.
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Highly competitive applicants will have training in nanomaterials research including synthesis, characterization, and assembly; or synthetic biology research and exposure to the underpinning knowledge tools such as genetic engineering, microbial engineering, bioinformatics; or machine learning research experience applied to the design of materials.
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Desirable skills/experience: Quantitative image analysis, some experience in artificial intelligence and machine learning, and hands-on experience in human neuroimaging and data analysis techniques such as MRI, fMRI, PET and EEG. Candidates with diverse experience and interests seeking to establish a career in neuroimaging are encouraged to apply.
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The position is designed to train recent graduates through working on exciting research projects to develop image reconstruction and image analysis techniques in multimodality imaging including PET/CT, SPECT/CT, and PET/MRI with a focus on integrating machine learning techniques.
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SUPPLY CHAIN MANAGEMENT (SCM) POSTDOCTORAL ASSOCIATE , Center for Transportation & Logistics (CTL)-Supply Chain Management (SCM) , to support the research and teaching activities related to streamline digital transformation, machine learning, and data analytics applied in logistics and supply chain management.
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Experience with machine learning methods and frameworks especially applied to physical science problems. The Scientific Software Engineering & Data Management Group in the X-Ray Science Division (XSD) at the Advanced Photon Source (APS) ( invites applicants for a postdoctoral position to develop and apply advanced analysis methods, including artificial intelligence and machine learning algorithms and approaches, for x-ray science and instruments.
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machine learning applied jobs Title: postdoctoral in Anoka, Minnesota
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