postdoctoral trainee

The International Society for Bayesian Analysis; Austin (TX); On-site; USD 52,000 - 70,000; Full time

Job summary

A renowned statistical research institution in Austin is seeking a post-doc to work on developing innovative statistical methods in applied and computational Bayesian statistics. Candidates should possess strong training in statistics, experience with Bayesian computation, and programming skills. The position offers a term of 1 to 3 years and focuses on biomedical research. Applications are due by December 1, 2019.

Qualifications

• Strong theoretical training in statistics or biostatistics required.
• Experience with Bayesian computation methods expected.
• Proficiency in programming and interest in publishing are essential.
• Interest in biostatistics and bioinformatics is a plus.

Responsibilities

• Develop innovative statistical methods for biomedical data.
• Conduct research in applied and computational Bayesian statistics.

Skills

Strong theoretical training in statistics/biostatistics

Good knowledge of Bayesian computation methods

Strong programming skills

Interest in publishing statistical methodology papers

Nonparametric models

Education

PhD in Statistics or Biostatistics

Tools

R

C or equivalent

Job description

The University of Texas at Austin,
Dpt. of Statistics & Data Science

Post-Doc Position Available Immediately

The Department has one post-doc position open for statistics research in applied and computational Bayesian statistics. The main focus is in developing innovative statistical methods and tools for the analysis of data arising in biomedical research problems. The term can range from one to three years.

Research Interest / Qualifications: Strong theoretical training in statistics/biostatistics; Good knowledge and some experience in Bayesian computation methods is required; strong programming skills; interest in publishing statistical methodology papers. Interest in biostatistics and bioinformatics is a plus.

Skills/Expertise in some of the following areas: Bayesian computation including MCMC, R, C or equivalent, simulations, nonparametric models and methods is a plus, statistical computation and graphics, biomarkers, genomics, proteomics.

Interested applicants should contact by December 1, 2019: