Post Doctoral Research Associate

Postdoc Fellow Opportunities – Using Across-phyla Methods to Increase Genomic Prediction Accuracy to Improve Health and Food Security

As part of Purdue’s growing investment in the life sciences, our recently funded research team is looking for two 3-year Postdoctoral Fellows to work in the area of genomic modeling of complex traits related to health and resilience in humans, livestock, or plants. The successful applicants will work under the supervision of Dr. Robbee Wedow (Department of Sociology, College of Liberal Arts), Dr. Matthew Tegtmeyer (Department of Biological Sciences, College of Science), Dr. Mitch Tuinstra (Department of Agronomy, College of Agriculture), and Dr. Luiz Brito (Department of Animal Sciences, College of Agriculture). Drs. Wedow, Tegtmeyer, Tuinstra, and Brito at Purdue University will be supported by a recently-funded Life Sciences Summit award that will fund each postdoc’s salary and benefits for up to 3 years. We are interested in candidates with expertise in computational and statistical genetics, quantitative genomics, and/or multi-omic data. The first postdoc, housed in the College of Liberal Arts/College of Science, should have expertise in human genetics/genomics. The second postdoc, housed in the College of Agriculture, should have expertise in plant or animal breeding genetics/genomics. The two postdocs will be expected to work together and lead projects aimed to develop and improve across-phyla methods to increase genomic prediction accuracy through the integration of multi-omic and large-scale phenotypic datasets in order to improve health and resilience in plants, animals (livestock), and humans.

Candidates should have a PhD in a relevant field (e.g., Animal Breeding, Plant Breeding, Quantitative Genetics, Genomics, Statistics, Statistical Genetics, Computer Science, Computational Biology) or another related field. Experience in R, Python, Fortran, or C/C++ and genetic/genomic packages (e.g., BLUPF90, GCTA, PLINK, ASREML) are needed. Experience with data analytics of high-throughput phenotypes and genomic prediction, with interfacing with cluster and cloud computing environments, and with data integration across biological data types is preferred. Preference will be given to candidates with a strong publication record and good scientific communication skills. 

The successful candidate will be responsible for: developing and implementing analytical pipelines for data editing/filtering and data integration, quantitative genomic analyses of complex traits using genomics and other omics data sources; developing and/or comparing statistical models, with a focus on machine learning methods, for more accurate predictions of polygenic risk scores, genomic breeding values (livestock and plants), and future phenotypes; evaluation of alternative models for studying the underlying biological mechanisms associated with phenotypic variability in complex traits based on genome-wide association studies (GWAS), transcriptome-wide association studies (TWAS), and others, including analyses of time-dependent traits; development of open-access sharing of tools – curation of code and tools; and interpretation of research results and preparation of extension articles and scientific papers. The researcher will also be expected to contribute to new research directions and drafting research proposals, and training of Undergraduate and Graduate students.

The initial appointment will be for one year, and extension for the second and third years will depend on their research performance. Salary and benefits are competitive and commensurate with qualifications. For submitting your application or enquiring further information about the research projects or the position, please contact Dr. Robbee Wedow ([email protected]), Dr. Matthew Tegtmeyer ([email protected]), Dr. Mitch Tuinstra ([email protected]), or Dr. Luiz Brito ([email protected]). Applicants should submit a cover letter, CV, and contact information of three references.

Screening of applicants will begin on March 1, 2024, and continue until the positions are filled. A background check will be required for employment in this position.

All individuals, including minorities, women, individuals with disabilities, and veterans are encouraged to apply.