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Field
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interested in working at the boundaries of several research domains Master's degree in computational biology, bioinformatics, systems biology, bioengineering, chemical engineering, or a related discipline
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in inorganic synthesis and/or Schlenk-line preparations Experience with scientific programming (e.g., MATLAB, LabView) is advantageous Experience performing quantum chemistry computations (e.g., DFT
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practices. Qualifications: A PhD in the Social Sciences or the Humanities. Strong research and writing skills, demonstrated in the publication of multiple peer reviewed journal articles. Deep familiarity with
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alto University is where science and art meet technology and business. We shape a sustainable future by making research breakthroughs in and across our disciplines, sparking the game changers
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computational mechanics of composite materials, and should be enthusiastic to work in a collaborative project between industry and academia.Vacancy 3: PhD (4 years) or postdoc (3 years) on mechanical modelling
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Research Assistant/Associate in Photonics Integration of Graphene and Related Materials (Fixed Term)
on integrated GRMs. The successful candidate will hold a PhD (or be close to obtaining) in Applied Physics, Material Science, Nanotechnology, Chemistry or Electrical Engineering with experience in photonics
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Working Title PhD MSE - Research Assistant Location Edinburg, Texas College College of Engineering and Computer Science Department College of Engineering and Computer Science / Mechanical Engineering
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 hour ago
Requirements PhD in Pharmaceutical Sciences or directly related field Preferred Qualifications, Competencies, and Experience The Research Assistant Professor will have the following essential competencies
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-subsaturated air (but where no contrail was formed). Research Associate: Hold a PhD in Aerospace Engineering, Atmospheric Science, Physics, or a closely related discipline*, or equivalent research, industrial
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engineering, and hyperparameter tuning to produce resilient and high-performing models. · PhD in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field Strong track record