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Field
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will disrupt today’s most vibrant research frontiers: Embed model-based AI into self-supervised pre-training pipelines Finetune multimodal deep learning models that answer diagnostic questions about X
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of biosystems and for extracting knowledge from (vast) sets of biotech data. A core technology leveraged by researchers at the center is deep machine learning, targeting the development of innovative tools and
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. Qualifications Applicants must hold a PhD degree in electrical/electronics engineering, telecommunications or related field. Other requirements include: Strong background in wireless communication systems and
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SD-25157 RESEARCHER IN ATMOSPHERIC PLASMA TREATMENT OF METALLIC SURFACES FOR INDUSTRIAL APPLICATIONS
of metallic surfaces. The researcher will work closely with the industrial partner to build up a deep understanding on the mechanisms driving the surface modification and develop strategies to implement
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international academic conferences. Lab: https://keaslinglab.lbl.gov/ School: https://vcresearch.berkeley.edu/faculty/jay-keasling Qualifications Basic qualifications (required at time of application) PhD
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Research, and Meta. Responsibilities: The Postdoctoral Fellows will be responsible for leading ongoing innovative research projects. Examples include: The development of probabilistic deep learning models
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-based algorithms (e.g., GNNs, deep reinforcement learning) design and simulate dynamic models of megaproject systems prepare and submit journal articles to high-impact publications contribute
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). About the role The project's primary goal is to investigate how low-dose IL-2 affects the neuro-inflammatory process. You'll use advanced cellular immunology techniques to conduct deep phenotypic and
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learning at scale. Research directions include designing algorithms and methods for adaptive and personalised feedback, modelling learning behaviours with sequence and deep learning methods, and generating
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Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) Doctoral Degree (or foreign equivalent) in hand by September 1, 2025. Deep knowledge of functional materials and