Multiple Postdoctoral Associate positions are available in the laboratory of Dr. Yu-Chiao Chiu at the Department of Medicine, Division of Hematology/Oncology and UPMC Hillman Cancer Center at the University of Pittsburgh School of Medicine. The candidates will engage in bioinformatics research to systematically understand the biology of adult and pediatric cancers, to identify diagnostic and prognostic biomarkers, and to improve cancer therapy. Research topics include deep learning methods applied to single cell profiles and other high-throughput genomic and pharmacogenomic datasets. At the UPMC Hillman Cancer Center, the candidates will have the opportunity to build cross-disciplinary collaborations with clinical, translational, and basic scientists in order to bridge cutting-edge computational algorithms to unmet needs in precision oncology.
The Chiu Lab focuses on the development of state-of-the-art machine and deep learning models that integrate large genomic and pharmacogenomic data to study cancer biology and improve cancer therapy. Our latest publications are well-recognized by broad cancer and bioinformatics communities: Science Advances (doi:10.1126/sciadv.abh1275; highlighted by @NCIgenomics as the #1 paper of 2021), BMC Medical Genomics (doi:10.1186/s12920-018-0460-9; selected as Springer Nature Research Highlights in Genetics of 2019), and Briefings in Bioinformatics (doi:10.1093/bib/bbz144). The lab is actively funded by federal and intramural funds. Our ongoing NIH/NCI supported project focuses on deep learning of drug sensitivity and genetic dependency of pediatric cancers. Please visit our lab website www.chiu-lab.org/ for more information.
Career development opportunities
The PI has successful experience in acquiring the prestigious NIH/NCI K99/R00 Pathway to Independence Award and postdoctoral fellowships, as well as mentoring the F99/K00 predoc to postdoc transition award application. Candidates will receive dedicated mentorship on career development planning, career development awards, and postdoctoral fellowships such as the Hillman Postdoctoral Fellowships for Innovative Cancer Research (hillmanresearch.upmc.edu/research/hillman-fellows/postdoctoral/).
The University of Pittsburgh School of Medicine is ranked #5 in NIH funding. Pittsburgh has been consistently voted as one of the top livable cities in the US. The University of Pittsburgh is an Affirmative Action/Equal Opportunity Employer and values equality of opportunity, human dignity, and diversity, EOE, including disability/vets. The University of Pittsburgh requires all Pitt constituents (employees, trainees, and students) on all campuses to be vaccinated against COVID-19 or have an approved exemption. Visit coronavirus.pitt.edu to learn more about this requirement.
- Highly motivated and enthusiastic scientists who have recently earned a Ph.D. degree in bioinformatics, computational biology, biomedical/electrical engineering, computer science, or a related field.
- Strong experience in computational modeling of biological systems, large-scale cancer multi-omic datasets (TCGA, TARGET, CCLE, etc.), high-throughput drug and genetic screens (DepMap, GDSC, etc.), and common bioinformatics resources (NCBI, UCSC, Ensembl, etc.) is essential.
- Experience in deep learning, machine learning, single-cell and spatial omics, and image processing is highly desirable.
- Candidates must be proficient with Linux and multiple bioinformatics programming languages, such as R, Python, MATLAB, and Perl.
- Candidates must possess excellent written and verbal English communication skills.
Interested candidates should apply via join.pitt.edu (Requisition #22005469 under “Postdoctoral Associate Positions”) and submit their curriculum vitae, one-page research statement, and contact information of three references. Review of applications will start immediately and continue on a rolling basis until the positions are filled. Inquiries may be directed to Yu-Chiao Chiu, PhD, Assistant Professor (YUC250@pitt.edu). Individuals from underrepresented minorities or disadvantaged backgrounds are particularly encouraged to apply.