We are looking for highly motivated students and postdocs who are interested in computational biology and genomics. Potential candidates should have either a strong computational background and an interest in developing and/or applying algorithms and machine learning techniques to genomic problems; or a strong experimental background and an interest in combining laboratory work with computational analyses.
The Gordan lab is recruiting graduate students mainly through the following PhD programs:
- Duke Computational Biology and Bioinformatics (CBB)
- Duke Computer Science (CS)
- Duke Biostatistics (B&B)
- Duke University Program in Genetics and Genomics (UPGG)
- Duke Molecular Genetics and Microbiology (MGM)
Interested students should apply through the PhD programs above. Interested postdoctoral applicants should send a CV, cover letter, and contact information for three references to Raluca Gordan at raluca.gordan-at-duke.edu.
All trainees in our lab learn and use a range of computational and/or experimental skills to study regulatory interactions between transcription factors and DNA, and to develop quantitative models of transcriptional regulation.
Typical computational skills include: developing data analysis tools using Python or R (or your favorite programming language); designing and implementing classification, regression, and clustering algorithms; processing genomic data to design DNA libraries for PBM experiments; developing statistical methods to analyze protein-DNA binding data.
Typical experimental skills include: gene cloning, DNA and protein quantification, site-directed mutagenesis, protein expression and purification, measuring in vitro protein-DNA binding using protein binding microarrays, mammalian cell culture, reporter assays.