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, an unofficial transcript or copy of the student academic records printed by the applicant or by academic advisors from internal institution systems may be submitted. Click here for detailed information about
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. Cross-Disciplinary Fellowships (CDF) are for applicants with a Ph.D. from outside the life sciences (e.g. in physics, chemistry, mathematics, engineering or computer sciences), who have not worked in
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Postdoctoral Scholar Position in Neuroethics or Techethics, Dept. of Engineering Science & Mechanics
. Approval of remote and hybrid work is not guaranteed regardless of work location. For additional information on remote work at Penn State, see Notice to Out of State Applicants . This is a term position
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. Approval of remote and hybrid work is not guaranteed regardless of work location. For additional information on remote work at Penn State, see Notice to Out of State Applicants . This is a term position
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. Approval of remote and hybrid work is not guaranteed regardless of work location. For additional information on remote work at Penn State, see Notice to Out of State Applicants . This is a term position
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. Approval of remote and hybrid work is not guaranteed regardless of work location. For additional information on remote work at Penn State, see Notice to Out of State Applicants . This is a term position
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management Proven strong publication record in peer‑reviewed scientific journals Experience or strong interest in communicating scientific information to the general public Demonstrated excellent written and
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related field Preferred Qualifications: Expertise in experimental design and quantitative data analysis Strong written and verbal communication skills, attention to detail, and ability to work both
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) resume or CV, including contact information for three professional references (3) writing sample (not to exceed 35 pages) (4) transcript NOTE: Position tasks are generally required to be performed in
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techniques to solve pressing challenges in energy storage. The successful candidate will work in the Data Science and Learning division of the Computing, Environment, and Life Sciences directorate of Argonne