The Environmental & Water Resources Systems (EWRS) group—Patrick Reed, Lindsay Anderson, and Scott Steinschneider—at Cornell is looking for any talented Cornell students who may be interested in working with the group. For all of these openings, strong computational and mathematical skills are essential, with preference for programming experience in Python, Matlab, and/or C++. Successful candidates are expected to be highly motivated, to have good communication skills in oral and written English, and to work effectively as part of a multidisciplinary team.
- The application of stochastic optimization to renewable energy systems. The research will contribute to projects supported by the US Department of Energy and the Power Systems Engineering Reliability Consortium (PSERC), addressing the need to jointly operate transmission and distribution (or microgrid) systems to enable the use of responsive loads to achieve the highest penetration of renewables, including wind and solar power. Applicants should have a background in Operations Research, Applied Mathematics and/or Electrical and Computer Engineering, and an interest is developing skills in bi-level and/or stochastic optimization (EWRS contact Lindsay Anderson).
- Development of integrated models of food-energy-water (FEW) systems, for the purpose of identifying interactions, synergies and feedbacks between and within these systems. Applicants for this position should have a strong background and interest in system modeling, with specific experience in one or more of the relevant systems (EWRS contacts Lindsay Anderson; Patrick Reed).
- Hydroclimatology projects that examine flood risk on the Great Lakes, paleoclimate reconstructions of extreme precipitation in the West, and hydropower proliferation in the Andean Amazon. The ideal candidates will have a background in civil and environmental engineering, hydrology, or the climate sciences with expertise in computer programming and statistical analysis (EWRS contact Scott Steinschneider).
- New frameworks for balancing conflicting objectives in river basin operations and urban water supply planning under deep uncertainty. The ideal candidates will have strong statistical, mathematical, and programming backgrounds with direct experience in hydrologic modeling. (EWRS contact Patrick Reed).