The Department of Biomedical Informatics at the University of Arkansas for Medical Sciences (UAMS) has an immediate opening for a postdoctoral research position in bioinformatics. The research emphasizes the development of methodology for the analysis of omics data such as gene set and network analyses. One example is related to high-throughput transcriptomics studies and combining RNA-seq and microarray data to find prognostic biomarkers associated with cancer subtype classification and treatment outcome. The candidate will contribute to multiple projects as necessary, perform data analysis, and participate in methodology and software tool development. Highly motivated candidates are encouraged to apply. The position offers an excellent opportunity to conduct research in stimulating environment and to collaborate with bioinformaticians, biologists, and clinicians. Stipend level follows the NIH standards for postdoctoral trainees.
- PhD in bioinformatics, computer science, biology, statistics, mathematics, electrical engineering or a related discipline.
- Strong programming skills in R, matlab, C/C++, python, perl, or Java.
- Strong background in statistical methods, linear algebra, and pattern recognition algorithms.
- Strong presentation and written/verbal communication skills.
- Experience using high performance computing (HPC) under UNIX/LINUX environment and creating job containers using Singularity or Docker.
- Ability to develop novel computational methods, algorithms and data processing pipelines.
- Background in machine learning, predictive modeling, and survival analysis.
- Some knowledge of stochastic simulations and network/graph analysis.
- Proven record of scientific publication in peer-reviewed journals.
Please submit CV with the names and contact information of three academic references, to Dr. Yasir Rahmatallah (firstname.lastname@example.org). The position will remain open until filled. Successful candidates will be contacted for interview. The University of Arkansas for Medical Sciences is an Equal Opportunity Employer.