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close collaboration with a deep-tech startup. You will work in an internationally recognized research environment with access to state-of-the-art cleanroom facilities and collaborate with leading academic
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Łukasiewicz Research Network – PORT Polish Center for Technology Development | Poland | 2 months ago
. The candidate will join ongoing projects in our team and perform mathematical/computational modeling. The topics include (1) constructing deep learning-based models to predict the molecular microenvironments
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
following areas: High-dimensional probability and concentration/functional inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations
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connection with the legal adoption of an eligible child, such as travel or court fees, for up to two adoptions in your household. To learn more, please visit: https://www.hr.upenn.edu/PennHR/benefits-pay
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PhD candidate who shares our deep interest in exploring conceptual, educational, social, and governance issues that emerge in the context of scientific modelling. The candidate also brings the following
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future. Fuelled by curiosity and a deep sense of responsibility, they provide invaluable contributions to research and teaching, thus enriching our society. Are you also inspired and driven by the desire
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Context Recent advances in computer vision and generative AI have enabled major breakthroughs in image and video understanding. However, modern deep learning models remain critically dependent
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). The applicant’s experience must be related to the tasks to be conducted, to the job description herein or to: · Training of multimodal models based on deep learning and GPU computing. · Evaluation and deployment
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, procurement, or grant administration will be an added advantage. Experience in areas such as Machine Learning, Deep Learning, Computer Vision, Large Language Models, Data Analytics, or Intelligent Systems will
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collaboratively with the Community Engagement unit/DICE. · Coordinating partner presentations with faculty and program directors to ensure alignment with academic learning goals. Data, Evaluation & Reporting