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neoclassical tearing modes in metal-wall scenarios; support the creation and validation of machine learning (ML) and hybrid physics + ML models to monitor and control the proximity to stability boundaries
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, color, ancestry, religious creed, gender identity and expression, national or ethnic origin, sex, sexual orientation, pregnancy, age, genetic information, disability, military or veteran status or any
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Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig | Leipzig, Sachsen | Germany | about 1 month ago
, the relation between human cognition and machine learning, and others. The position is offered for three years. The starting date is, in principle, flexible, while we aim to get started as soon as possible
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tolerance for varietal selection. Learning Objectives: Participant will gain laboratory, field, and programming skills to develop the digital twin and other AI models using ground and above-ground sensors and
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Current Employees: If you are a current Staff, Faculty or Temporary employee at the University of Miami, please click here to log in to Workday to use the internal application process. To learn how
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, biochemical, cell, and tissue biology method skills. Experience in using computational analysis (biostatistics, machine learning, data science, physics, or a related field). We value diversity and strongly
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platforms include GRO-seq, RNA-seq, ChIP-seq, ATAC-seq, CRISPR-seq, single-cell RNA/ATAC-seq, microC, machine learning, sophisticated mouse genetic tools, and an ex vivo tissue culture system from patients
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About the role We invite applications for a Postdoctoral Research Assistant to be part of a new research project ‘Innate and Learned Proficiencies in Facial Age Estimation’. The project is funded by
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converter degradation/failure analysis. Brief Description of Duties: The Postdoctoral Associate will support the Principal Investigator, Dr. Fang Luo , in the Department of Electrical and Computer Engineering
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approaches. What we ask of you Required PhD in machine learning, physics, or a related field. Established expertise in deep learning (familiarity with graph neural networks, transformers, diffusion and flow