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Postdoctoral Fellowship in Theoretical Condensed Matter Physics. This prize fellowship is designed to attract the best and brightest theoretical physicists within 3 years or their PhD to work with theorists and
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conditional on satisfactory performance and funding. Requirements PhD in quantitative ecology, applied statistics, or a related field with strong background in statistics and model development. Experience with
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. Applications will be reviewed on a rolling basis beginning October 1 until the position is filled. Candidates must be able to provide proof of PhD prior to appointment start date. The project is primarily funded
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. (5%) Term of position This is a one-year appointment, renewable on a year-to-year basis up to three years conditional on satisfactory performance and funding. Requirements ● PhD in quantitative ecology
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conditional on satisfactory performance and funding. Requirements PhD in quantitative ecology, applied statistics, or a related field with strong background in statistics and model development. Experience with
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your cover letter, including which Shima Seiki machine you operated, how long have you worked with the machine, and for what purposes/projects, PhD degree in Computer Science, Electrical Engineering
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, how long have you worked with the machine, and for what purposes/projects, · PhD degree in Computer Science, Electrical Engineering, Information Science, Mechanical Engineering, Human-Computer
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Requirements A PhD in Biochemistry, Molecular Biology or Cell biology. A requirement for the position is evidence of peer-reviewed publications in a related field, and general enthusiasm for science. Skills
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for presentation 10% of the employee’s time will involve the mentoring of undergraduate or graduate students 10% of the employee’s time will involve professional development Requirements A PhD in Biochemistry
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Requirements A PhD in Biochemistry, Molecular Biology or Cell biology. A requirement for the position is evidence of peer-reviewed publications in a related field, and general enthusiasm for science. Skills