A cancer genomics post-doctoral position is available at The Ohio State University working in an exciting position between tenured physician scientists or translational PhD scientists in the Division of Hematology and Sucheston-Campbell labs focused on genetic susceptibility to leukemia and lymphoma etiology and treatment outcomes. The Division of Hematology has a wide breadth of clinical translational material from leukemia and lymphoma patients and has undertaken several large genomic projects to move efforts forward to impact the lives of individuals with these diseases. As a Postdoctoral Fellow you will use your knowledge and skills in biostatistics and genomics to analyze and interpret data generated from genomics experiments including gwas, whole exome and genome sequencing, ChIP-seq, RNA-seq or bisulfite sequencing. The post-doctoral fellow will gain considerable bi-directional mentorship in translational experimental therapeutics and computational biology by bridging collaborations between these two groups. Based upon the project chosen, the post-doctoral fellow will work with a tenured faculty member from the Division of Hematology as a co-mentor in conjunction with co-mentor Dr. Sucheston-Campbell, an Associate Professor and genetic epidemiologist in the Colleges of Pharmacy and Veterinary Medicine. All of the hematology faculty members included in this program and Dr. Sucheston-Campbell enjoy mentoring graduate students and postdoctoral fellows who are interested in expanding their genomic computational skills and contributing to leukemia research.
You will be encouraged to expand your knowledge of computer programming, statistical methods and cancer biology by attending seminars, national research meetings and short-courses. You will be provided mentorship on performing highly impactful research, paper writing, and grant preparation. The Ohio State University offers excellent benefits and is situated in Columbus, the thriving capital of the State of Ohio.
To assist in the design of genomics experiments with proper controls and statistical power.
To perform quality control analyses of genomic data, including quality control scripting for high throughput experiments.
To help identify, annotate and visualize genomic variation associated with outcomes and etiology leveraging existing computational resources in R (Bioconductor, ShinyR), stand-alone programs and publically available data, for example: ANNOVAR, SeattleSeq, VEP, 1000G, TCGA, COSMIC, GEO, GDS, Oncomine, Cistrome, Gtex
To work towards developing independent scientific ideas with the goal of writing post-doctoral appropriate research grants (R03, K-award spectrum) with eventual development of independent investigator status
A doctoral degree (PhD, DSc) degree in Genetic Epidemiology, Biostatistics, Statistics, Bioinformatics, Computational Biology, Computer Science, Physics or a related field.
Expertise in R and R/Bioconductor and a scripting language (perl, python) in a Unix server environment,
An interest in working with a diverse array of scientists to develop a better understanding of cancer through the synergy of wet and dry lab approaches.
Please send CV and 1 page research statement to: firstname.lastname@example.org