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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
to develop hybrid models for sea ice that combine coupled climate models and machine learning. Our previous work has demonstrated that neural networks can skillfully predict sea ice data assimilation
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mechanics, molecular dynamics, and data science tools to study the mechanisms of catalytic organic reactions and enzymatic reactions. Job Qualifications: · PhD in Computational Chemistry, Organic
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22.03.2021, Wissenschaftliches Personal The 3D AI Lab at the Technical University of Munich is looking for highly motivated PhD students and PostDocs at the intersection of computer vision, machine
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). Below are key aspects of the training program: The Yale CPC Training Program aims to train pre- and post-doctoral fellows in five thematic areas: cancer etiology, cancer outcomes, lifestyle behavioral
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Required Knowledge, Skills, and/or Abilities Demonstrated experience in computation/computer algorithms, as evidenced by relevant publications. Desirable Knowledge, Skills, and/or Abilities Proficiency in
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | about 1 month ago
learning. It also offers the opportunity to work with data from the European XFEL facility at DESY. Project website Your profile Eligible candidates have strong skills in computational physics and
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in a manner that supports a research-led and scholarly approach to student learning and assessment in the discipline and/or profession. 3. Participate fully in examination and other assessment
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relevant field at the PhD level with zero to five years of employment experience. Experience with deep learning frameworks (PyTorch, TensorFlow, JAX). Strong background in computational image processing and
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) -Institute of Fundamental and Frontier Sciences -RF [#30238] Position Title: Position Type: Postdoctoral Position Location: Chengdu, Sichuan, China Subject Areas: Physics / Quantum Computation Quantum
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develop and apply computational approaches for mass spectrometry data, with artificial intelligence/machine learning (AI/ML) being a major focus. They will have an opportunity to lead and contribute to a