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Field
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opportunity promises deep academic inquiry, industry collaborations, and the chance to influence future practices and research directions in these fields. Key Responsibilities: Develop robust mathematical and
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of infrastructure and technology systems for mathematical/computational modeling and control theory for life-cycle management optimization and policy of smart and sustainable infrastructure and environment systems
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ICFO is offering a postdoctoral position to outstanding, highly motivated scientists, who wishes to contribute advance technologies that drive the clean energy transition. In particular, we seek to develop novel strategies that contribute overcoming critical resource bottlenecks in energy...
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. Proficiency in frameworks like Pyomo and/or TensorFlow/Pytorch/Keras Solid foundation in mathematics/statistics, with experience in cyber-physical systems modeling. Ability to work both independently and
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approaches to problems in acoustics, lasers, spectroscopy and atomic beams. Our faculty collaborate with colleagues in many other units including Biology, Chemistry, Mathematics and the Brody School
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, LROC, ROC, Image perception, mathematical/computational observer models. Both experimental and computational positions available. Skills preferred include any of these: Monte Carlo simulations, benchtop
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large amount of data, using advanced statistical techniques and mathematical analyses. Manage analytical projects from data exploration, model building, performance evaluation, through implementation
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computer programming tools such as Matlab and/or Python. Knowledge of statistics and mathematical modeling. Experience in large spatial data processing, analysis, and interpretation. Experience in running
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. Contribute to the supervision of Master’s and Ph.D students. Qualifications Ph.D. in Artificial Intelligence, Data Science, Climate Science, Geoinformatics, Applied and Computational Mathematics, or related
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-channel electrophysiology •Any prior work in mathematical models of decision-making •Prior work with psychiatric patient populations or the biological mechanisms of mental illness About the Department