48 computational-mathematics-phd Postdoctoral positions at Pennsylvania State University
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Computer Science, Math, Statistics (in hand at time of hire) or a related field are eligible to apply. Life sciences (Biology, Genetics, Biochemistry, etc.) PhDs with computational experience are also
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students. The required qualifications are: PhD degree in mathematics, science, engineering, or a related field by the start date. Extensive experience in one or more of the following areas: probabilistic
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reporting. Candidates must have a PhD in MatSE and experience in mechanics of materials, computational modeling, and experimental characterization of materials. Candidates should submit a CV and cover letter
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. Requirements and Qualifications: The Postdoctoral Scholar must have a PhD in transportation engineering, operations research, mathematics, or a related field by the appointment start date. In addition, the
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functional magnetic resonance imaging: fMRI) methods to investigate iconicity in spoken language – the idea that the sound of a word may convey its meaning. The successful candidate will have a PhD in a
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satisfactory performance. Degree/Field of Study: PhD in fluid dynamics, geomechanics, computational geomechanics by start date with Penn State. Applications must be submitted electronically and include a CV
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medicine program is a collaborative research effort that offers many opportunities for scientific interactions and advancement. Duties include (but are not limited to): Designing and executing experiments
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. JOB DESCRIPTION AND POSITION REQUIREMENTS: The Eberly College of Science, Department of Physics at The Pennsylvania State University is seeking to fill one postdoctoral scholar position in computational
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a Ph.D. in computer science, engineering, mathematics, or other related fields. Successful candidates must have Ph.D. or terminal degree prior to beginning employment at Penn State. This appointment
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, Robotics, Computer Vision, or related disciplines. Proven expertise and hands-on experience in one or more of the following areas: large language models (LLMs), end-to-end learning, AV localization