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Dear CAST Colleagues, Several Postdoctoral/Research Fellow openings (or research engineer/associate for master degree holders) are currently available at the National University of Singapore (NUS). Please find the detailed job descriptions below: 1. Computational Global Optimization with Chemical Engineering Applications: Applications requested for Research Fellow (Postdoc) positions on computational optimization of chemical engineering problems with Prof. Christine Shoemaker, Distinguished Professor in the Department of Industrial and Systems Engineering, who is working with Chemical Engineering Faculty (Chi-Hwa Wang and Xiaonan Wang). The application is on optimizing waste to energy processes to improve environmental sustainability. The project will develop, implement and/or evaluate serial and parallel optimization algorithms for simulation models arising in chemical engineering and/or apply the algorithms to complex engineering problems. The candidate will have the opportunity to develop research skills, improve domain knowledge and expertise, attend international conferences, and work on the new Singapore Supercomputer (NSCC). Professor Shoemaker (PhD in mathematics, member of the US National Academy of Engineering and Fellow in the: SIAM, INFORMS, AGU, and ASCE) was Ripley Professor at Cornell University in US before coming to NUS. Requirements: A PhD degree in Chemical Engineering, or in an optimization/statistical/numerical analysis field (e.g. Operations Research, Industrial/Systems Engineering, Statistics, and Applied Mathematics), or in Computer Science is sufficient. (Candidates about to complete their PhDs may also apply.) Experience in developing complex computer codes, preferably in Python or C++ and knowledge of nonlinear (local) optimization or surrogate global optimization is desired. Some knowledge of numerical methods for solving partial differential equations is preferred. Ability to construct and write papers for leading research journals and conferences is essential. 2. Decision Support Systems for waste to energy and resources: A circular economy will bring significant environmental and economic benefits by using material and energy recovery through waste streams to provide support for carbon capture and substitute fossil fuels. The project includes the following components: 1) Review literature and compare current waste treatment and energy structures in several mega cities (e.g., Singapore and Shanghai); collect and analyse relevant data. 2) Modelling, optimization, and deployment of advanced computational methods/tools to study waste-to-energy and waste-to- resource. 3) Deliver and disseminate the decision support tools and results to government agencies. The project will link directly with the ongoing research carried out at the CREATE "Energy and Environmental Sustainability Solutions for Megacities (E2S2)" program, together with various academic, governmental and industrial agencies. We offer the opportunity to work on an exciting multi-disciplinary case with potential real-world applications. Requirement: The candidate should have strong interest and capability in programing (e.g., C#, Python), environmental and economic analyses and be proactive, organized and willing to learn different tools and communicate with different teams, better with high-quality publications on relevant topics before. At least a Masterís Degree in science or engineering is required. PhD degrees in chemical engineering, environmental science and engineering, mechanical engineering etc. are preferred. Except for related research experience, a critical skill of software development, modelling and optimization is highly recommended for the position. 3. Quantitative methods for advanced materials development: This project will deploy advanced data mining, machine learning/deep learning and other computational strategies to accelerate understanding of functional materials synthesis (e.g., nanoclusters) and redefine the best practice of design of experiments. The researcher will work closely with our experimental and industrial collaborators to apply advanced AI technologies on the computing platform, in collaboration with international collaborators. The project will link directly with the ongoing research at the Accelerated Materials Development program http://acceleratedmaterials.org/, as well as the Smart Systems Engineering (SSE) group. Requirement: The candidate should have strong interest and capability in machine learning, programing and be willing to lead and communicate with different teams. At least a Masterís Degree in science or engineering is required. PhD degrees in chemical engineering, materials science and engineering, and computer science etc. are preferred. We expect the candidates to start as soon as possible, but starting in 2019 is also possible. The openings are continuously available but applications received by October 28, 2018 will receive prioritized consideration. English is the language for Singapore and NUS. Top candidates may be recommended to highly competitive salary scale and positions. Interested applicants should send a cover letter, detailed curriculum vitae, and selected publications to be emailed directly to Dr Xiaonan Wang at [log in to unmask] Best regards, Xiaonan --- Xiaonan Wang Assistant Professor National University of Singapore (NUS) Department of Chemical and Biomolecular Engineering Tel: +65 6601 6221 Email: [log in to unmask] Group Website: http://www.smartsystemsengineering.com/