10 software-verification-computer-science research jobs at University of Texas at Austin
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, advanced optimization and control of semiconductor manufacturing processes and systems. Experience in working with advanced AI/ML software packages and super-computing cluster systems, including Hadoop
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collection, including cognitive assessments such as computer-based testing, questionnaires, and health measurements, as well as brain measures such as electroencephalography and near-infrared spectroscopy
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. Required Qualifications · PhD in Geophysics · Experience with land seismic acquisition, DAS, and time-lapse monitoring · Proficient in computer programming · Extensive publication and presentation record
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knowledge Masters new assessment tools and software Adapts to evolving research protocols Applies neuropsychological concepts in practice Integrity and Trust Is widely trusted and maintains confidentiality
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transfer, fluid mechanics, and interfacial sciences. Experience with experiments and modeling (traditional CFD modeling). Experience with finite element analysis and/or software packages like Comsol or ANSYS
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at SEG, EAGE, AGU, SPWLA, or similar conferences. Experience in writing professional-level programing codes as well as working with industry-standard software. Salary Range $65,000 - $70,000 Working
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to have exceptionally strong backgrounds in GIS, computational science and expertise in other sciences (biology, ecology, physics/engineering, etc.) and programming (e.g. R, Python, etc.). The successful
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thinking skills, and ability to work as part of a multidisciplinary team. High computer proficiency, including basic MS Office, MS Access, graphics, and database software. Basic project management and
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thinking skills, and ability to work as part of a multidisciplinary team. High computer proficiency, including basic MS Office, MS Access, graphics, and database software. Basic project management and
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with incoming Assistant Professor Dr. Adela Timmons. Research in the TIES Lab focuses on big data analytics and pervasive computing methods for building adaptive and responsive mental health