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Digital Twin for electric vehicle applications . The role will focus on utilizing novel machine learning models, large language models, and data science algorithms to develop battery models, optimization
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maintenance of both mammalian and microbial cells Devise micro-bioreactor for co-culture of mammalian and microbial cells Program control algorithm for optical sensors Design, fabricate, and optimize
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algorithms, including machine unlearning techniques, to enhance model robustness and reliability. Design and execute rigorous AI testing frameworks to assess and mitigate risks in AI systems. Collaborate with
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Responsibilities: Development of stochastic and analytical methods for nonlinear partial differential equations Implementation of relevant numerical experiments using deep learning algorithms Job Requirements: PhD
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or Mathematics or Statistics with a strong background in one or more of the following: AI, machine learning, Bayesian statistics, programming languages, logic and algorithms, formal methods, probability and
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and develop machine learning and mathematical optimization solutions for electric vehicle (EV) fleet charging scheduling problems with considerations of various smart power grids, battery degradation
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project KPIs and objectives per grant management. Ensure milestone delivery per plan/schedule, manage/control project risks & mitigating actions Prepare/consolidate monthly and annual periodic reports
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literature reviews Plan the necessary logistics, for the administration of experiments and focus group sessions, such as scheduling, booking facilities, and preparing IRB documentation Participate in the data