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(bio-)chemistry, physics, and engineering expertise to study molecules and cells, taking advantage of optical and single-molecule imaging, molecular probes, molecular biology, and 'large' data analysis
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Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
publications and project reports Your Profile: Strong motivation for an interdisciplinary project that combines numerical models, experiments, and artificial intelligence A master`s degree or diploma in physics
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APPLICATION INSTRUCTIONS: CURRENT PENN STATE EMPLOYEE (faculty, staff, technical service, or student), please login to Workday to complete the internal application process . Please do not apply
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that demand interdisciplinary solutions? Then the Program for Collaborative Doctoral Projects is the perfect opportunity for you. Many of today’s most pressing problems can only be tackled through
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, Biomedicine, or Computational Systems Biology. Experience with NGS data or single cell-sequencing analysis is required. Competence in adipose tissue biology, cell culture work or mouse physiology would be
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people across disciplines and with a variety of perspectives and backgrounds. The Faculty has six departments: Biology, Pharmaceutical Sciences, Information & Computing Sciences, Physics, Chemistry and
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/physics/biology) or engineering. The ideal candidate should have some understanding in the areas of Materials Science, Chemistry, Physics, Metallurgy, or Mechanical Engineering. The candidate should be self
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biology: How do epigenetic features contribute to the regulation of the genome? We study how chromatin drives specificity for regulating gene expression. You will be dissecting the molecular features
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. The Faculty external link has six departments: Biology, Pharmaceutical Sciences, Information & Computing Sciences, Physics, Chemistry and Mathematics. Together, we external link work on excellent research and
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projects are multidisciplinary in nature, and the ideal candidates are comfortable with moving outside their field to understand both molecular biology and computational methods. We rely heavily