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Field
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Qualifications: Ph.D. or other terminal degree in terminal degree in Civil or Environmental Engineering, hydrology, ecology, geosciences, computer science, applied mathematics, data analytics, or related fields
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Join Our Team at the School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore The School of Physical and Mathematical Sciences (SPMS) at NTU Singapore hosts research
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individually, make a real difference. The role An exciting opportunity for a postdoctoral Research Fellow with a background in mathematical modelling / epidemiology has become available in the Faculty of Health
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research aimed at quantifying or modelling the state and function of soils across spatially variable landscapes. Applied experience in using statistical and mathematical tools to analyse and interpret soil
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A Junior Research Fellowship is intended for a researcher early in their career and, in this case, is restricted to applicants in one or more of the following subject areas: Classics History (restricted to work that falls substantially within the period c. 700–c. 1450) Music Politics &...
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background in landscape ecology, geography or even landscape architecture is helpful, the work is expected to lean heavily on mathematical, statistical and quantitative analysis of the LiDAR data to not only
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The University of Surrey is a global community of ideas and people, dedicated to life-changing education and research. We are ambitious and have a bold vision of what we want to achieve - shaping ourselves into one of the best universities in the world. Our culture empowers people to achieve...
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this aim and to collectively, and individually, make a real difference. The role An exciting opportunity for a postdoctoral Research Fellow with a background in mathematical modelling / epidemiology has
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performing other duties that support the efficient operation of the research team. Mandatory: PhD or equivalent in electrical and electronic engineering and/or applied mathematics, in particular, in one
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robotics systems. • Strong mathematical background with solid knowledge in numerical optimization theory. Familiarity with semidefinite programming and its convex relaxation techniques is highly preferred