Computational Biologist

1 month ago

Richmond, Virginia, United States Commonwealth of Virginia Full time
Job Title: Assistant Professor of Computational Biology

Virginia Commonwealth University is seeking a highly qualified Assistant Professor of Computational Biology to join our team. As a member of our faculty, you will play a key role in advancing our research in cancer biology and developing innovative computational approaches to understand the mechanisms of cancer.

Job Summary:

The successful candidate will have a strong background in computational biology, bioinformatics, and systems biology, with a proven track record of research experience in the fields of genomics, proteomics, and/or systems biology. You will be responsible for leading research projects, mentoring graduate students, and teaching courses in computational biology and bioinformatics.

Responsibilities:
  • Lead research projects in computational biology and bioinformatics, with a focus on understanding the mechanisms of cancer.
  • Mentor graduate students in computational biology and bioinformatics, providing guidance and support in their research projects.
  • Teach courses in computational biology and bioinformatics, including team-teaching medical and graduate-level courses.
  • Collaborate with faculty members in the department of pharmacology and toxicology, as well as with researchers in other departments and institutions.
  • Develop and submit grant proposals to secure funding for research projects.
Requirements:
  • Ph.D. in Bioinformatics, Computational Biology, or a closely related field.
  • 8 or more years of research experience in the fields of bioinformatics, computational biology, systems biology, proteomics, and/or genomics.
  • Deep understanding of Ras signal transduction pathways and experience in investigating the mechanism of KRAS addiction of cancer cells.
  • Extensive publication record in reputable scientific journals.
  • Proven trainee and faculty mentorship skills.
  • Track record of working in multi-disciplinary fields and fostering a diverse faculty, staff, and student environment.
Preferred Qualifications:
  • Design and analysis of genome/proteome-scale research, including differential gene/protein expression and pathway analysis.
  • Analysis and interpretation of high-dimensional data, including genomic, transcriptomic, and proteomic datasets.
  • Experience in cancer research field and/or drug discovery.
  • Experience working in a matrix environment within academic medicine.
  • Proven success in collaborating with multi-disciplinary teams.

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