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Field
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sciences or engineering with research experience in geothermal energy. Proven capacity for innovative, creative scientific analysis Excellent data management skills Proven publication skills and verbal
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molecular biology and biochemical techniques such as cloning, in vitro transcription, nucleic acid purification, PCR, next generation sequencing library preparation and immunoblotting. Help prepare data
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opportunities for grant writing and collaborative writing projects are also possible. Qualifications Ph.D. in psychological sciences, human development, speech and/or language, neuroscience, biostatistics or a
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biology, demonstrated by publications in high impact journals. The person would be well versed with various techniques used in the field of cancer immunology as well as having the ability to plan, execute
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computational chemistry and biochemistry studies as directed by Prof. William Goddard within the Materials and Process Simulation Center in the Division of Chemistry and Chemical Engineering Essential Job Duties
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biology, biochemistry, cell biology, immunology, or microbiology Knowledge of computers, including Microsoft Word, Excel and PowerPoint. Working Conditions Lab Environment. Application Documents Resume
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on scientific problems, whether biomedical or other, and to applicants with a strong record of scientific productivity. The successful applicant must have a Ph.D. in Computer Science, Data Science, Statistics
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involved in analyzing data collected from the TexNet seismological monitoring program and other stations or assets that provide quality data. Comparing different methods and tools for moment tensor inversion
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as assigned. Key Qualifications: B.S. in molecular biology/biochemistry or related field with 7 years of relevant experience, or M.S. with 4 years of experience. Ph.D is preferred. Core Skills
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molecular biology and biochemical techniques such as cloning, in vitro transcription, nucleic acid purification, PCR, next generation sequencing library preparation and immunoblotting. Help prepare data