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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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skills. Strong analytical and communication skills; ability to work both independently and collaboratively. Desirable: Familiarity with modern in-process or embedded query engines (e.g., DuckDB, SQLite
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abilities are essential. The candidate should be capable of working both independently and collaboratively within a team. Applicants must have a PhD in chemical or process engineering, environmental
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will create a personalized training and development plan with the supervisor. Minimum Qualifications Currently has or is in the process of completing a PhD, MD/PhD, DPhil or equivalent terminal degree
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chemistry, physics, materials science, or a related field, with a focus on crystallography. To apply, submit a cover letter, a curriculum vitae that includes a complete publication list, a statement of
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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
following areas: Large-deformation numerical modeling (e.g., Coupled Eulerian-Lagrangian (CEL), Material Point Method (MPM), or advanced Finite Element Methods). Physical modeling of tunnel excavation and
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robots and competency in the Robot Operating System, and/or Physics Engine Simulators are preferred. The terms of employment are very competitive and include housing and educational subsidies for children
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Nadeem and Murat Uysal. Principal Responsibilities The PDA will conduct research on the physical layer and MAC layer design for wireless systems, particularly across multiple spectrum bands. The PDA is
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(PDA) to engage in cutting-edge research on the physical layer design of next-generation wireless communication systems, with a primary focus on 6G technologies. The research will particularly emphasize
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for physical systems. The postdoc will work on projects focusing on one or more of the following: Robot Learning & Autonomy – Developing algorithms that allow robots to learn (via exploration or imitation) from