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completed) in Natural Language Processing or a closely related area. Solid knowledge of machine learning, especially deep learning. Experience in model development and/or fine-tuning. A practical mindset
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spans computational materials design, catalysis, energy materials, machine learning, and artificial intelligence. We offer a collaborative and international research environment with close interactions
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Posted on Tue, 08/04/2026 - 10:36 Important Info Faculty Sponsor First name: Emmanuel Faculty Sponsor Last Name: Mignot Stanford Departments and Centers: Psychiatry Postdoc Appointment Term: 2 years
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, the Giustacchini group aim to develop stem-cell-based models of paediatric leukaemia to understand how malignant haematopoiesis interacts with the immune system and to improve responses to CAR T-cell therapy. We
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Organization National Energy Technology Laboratory (NETL) Reference Code NETL-Postdoc How to Apply A complete application consists of: An application, including academic history, work history
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chain, ranging from synthesis, cell assembly, characterization, modeling to scaled-up manufacturing. The 2-year postdoctoral project Machine Learning-based Electro-Chemo-Mechanical Estimation and Control
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cardiovascular care. Within the consortium, TU Delft contributes expertise in cardiac mechanics, soft tissue modeling, growth and remodeling, machine learning, and uncertainty-aware model personalization. As a
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pursue the use of machine learning techniques for data analysis. Candidates must have a Ph.D. and research experience in experimental high energy physics. The successful candidate is expected to carry out
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network inference and modeling, machine learning and deep learning. Experience in working with Arabidopsis and plant genome data is a strong plus. The position is expected to continue for multiple years
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Nutrition Postdoc Appointment Term: Fixed term for one (1) year with opportunity for renewal Appointment Start Date: ASAP Group or Departmental Website: https://colmanlab.stanford.edu/(link is external) How