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of the Water Research Center. The successful applicant will lead an innovative project focused on the development of hybrid processes for the recovery of minerals from desalination reject brine. The role will
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. RISC invites qualified applicants in the areas of electrical, computer, or mechanical engineering, or other related department to apply. The successful applicants will design controllers for a variety of
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. Contribute to the smooth operation of the laboratory. Participate in the academic activities of the division. This position does not include teaching duties and the SSEL provides financial support for travel
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background and expertise in one or more of the following areas: High-dimensional probability and concentration/functional inequalities Markov processes and stochastic analysis Theoretical analysis of neural
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processes. Developing and optimizing functional membranes, including electrically conductive membranes, for use in desalination, energy generation, and electrochemical separations. Responsibilities: Conduct
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competitive salary and benefits. Research in the SIT-D lab focuses on understanding and modelling consumers' behavior and decision process for sustainable transport modes and transport innovations. Research is
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. The successful applicant will contribute to four main research thrusts that are central to the success of this multidisciplinary project: (i) designing and developing chemical and ion-exchange processes for energy
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through computer simulations and/or experimental validation. The PDA is expected to actively disseminate results through publications in high-impact journals and presentations at leading international
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well as familiarity with machine learning workflows, natural language processing (NLP), and text-as-data methods. We are especially interested in applicants who demonstrate a strong substantive interest in using
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natural language processing and machine learning workflows; (3) experimental design and causal inference (including virtual lab experiments); and/or (4) network or computational modeling. The ideal