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investigations. Qualifications: Ph.D. or equivalent degree in Biomedical Engineering, Electrical Engineering, or a related fieldStrong background in MR physics Proficiency in computer programming Excellent written
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) Chemistry and Materials Sciences (12 ) Computer, Information, and Data Sciences (17 ) Earth and Geosciences (21 ) Engineering (29 ) Environmental and Marine Sciences (14 ) Life Health and Medical
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pipelines for 16s rRNA and WGS sequence data from pathogens. Advanced computer programming skills in R and Python and preferably also other languages and demonstrated proficiency in UNIX, shell scripting
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Qualifications: Ph.D. in electrical, electronics, or VLSI engineering; computer engineering; computer science; computational science; or a closely related field completed within five years of application Strong
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 1 month ago
Posting Description POSTDOCTORAL ASSOCIATE, Mechanical Engineering, to perform cutting-edge research on projects centered around machine learning models for Computer Aided Design and Engineering
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-the-loop exploration of extreme-scale scientific data. This position sits at the intersection of scientific visualization, agentic AI systems, human–computer interaction (HCI), and high-performance computing
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to efficiently collect/organize/analyze data and initiate new/modified procedures/techniques based on the latest developments are expected. Certificates/Credentials/Licenses n/a Computer Skills General office
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. Certifications/Licenses Required Knowledge, Skills, and Abilities Excellent written, verbal and computer skills required. Excellent communication and interpersonal skills. Must be able to work independently and/or
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of a collaborative, multidisciplinary team Computer Skills: Demonstrated ability to do electronic scheduling and record keeping Preferred Qualifications Specialization in an area pertinent to CSUF
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Computer Engineering within the USC Viterbi School of Engineering. The ideal candidate will have an extensive background in one or more of the following areas: Information theory, structured statistics