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Field
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skills and experience: Essential criteria PhD qualified in relevant subject area* Experience developing deep learning segmentation models Experience with Pytorch, MONAI, CUDA or equivalent software
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learning. The post-holder will be familiar with the use of these techniques and experience of dataset construction and data mining will be essential. The successful applicant will have completed an MPhil/PhD
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vision research. The department fosters interdisciplinary collaboration, addressing real-world challenges through innovative machine learning, data science, and intelligent systems research. About the role
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sufficiently versatile to rapidly acquire the required capacity. You will have : A PhD in gut microbiology or closely related field Good knowledge of gut modelling and general microbiology Experience in
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Education and/or Work Experience M.D. or PhD Required Qualifications Ph.D. in any of the following areas: Neuroscience, Pharmacology, Physiology, or Biochemistry. Certificates/Credentials/Licenses Ph.D. in
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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high intellectual merit and the willingness to use machine learning and/or AI techniques. Essential Duties and Responsibilities: Successful candidates are expected to develop an impactful research
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Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning, statistics, data science, applied math and/or other
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that the candidate has prior research experience in one or more of the following research topics: Free space optical communication Visible light communication DSP for coherent optical communication Machine learning
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superconducting qubits and millikelvin electronics Did you recently get your PhD in circuit quantum electrodynamics (cQED) and are now looking into taking the full potential of your skills into use for making new