Postdoctoral Associate - BioSciences

Dr. Lauren Hennelly’s lab in the Department of Biosciences seeks to hire a Postdoctoral Research Associate in the field of Evolutionary and Conservation Genomics.

The Hennelly Lab is hiring a Postdoctoral Research Associate in evolutionary and population genomics in mammalian systems. The project will involve analyzing genomic data from modern and historical/ancient genomic datasets, and using computational methods to assess patterns and evolutionary consequences of hybridization between different canid species. The initial contract is 1 year and renewable for 1 extra year.

Our lab studies the evolutionary processes that shape genetic and phenotypic variation in animals. We integrate population genomic data, museum and ancient DNA, fieldwork, and phenotypic data to investigate the evolutionary histories of species, how anthropogenic change alters evolutionary trajectories of species, and the molecular basis of complex and adaptive traits ( https://hennellylab.com/ ).

Special Instructions to Applicants: All interested applicants should attach a resume in the Supporting Documents section of the application, preferably in a PDF format to avoid any formatting issues.

All interested applicants should apply through the job posting and also email the following materials to Dr. Lauren Hennelly at lh106@rice.edu:

A one-page cover letter describing their research experience, career goals, and interest in the position

CV

Contact information for three references

Ideal Candidate Statement: The ideal candidate will be a highly motivated postdoctoral research associate with strong experience in computational and bioinformatic methods, population genomic analysis, and an interest in addressing fundamental questions in evolutionary biology, including speciation, adaptation, and consequences of hybridization in mammalian systems. The postdoctoral researcher will have opportunities to collaborate with researchers, external collaborators, and PhD students in the Hennelly Lab. The position is designed to support the candidate’s professional development through opportunities in scientific publishing, grant writing, student mentorship, and scientific outreach.

Workplace Requirements:

In-person work in Houston is preferred. However, we offer the flexibility of hybrid or fully remote work. Please note that fully remote eligibility is limited to residents of approved states. Hybrid roles integrate on-campus and remote work to foster both independence and collaboration. In accordance with Rice Policy 440 , work arrangements are subject to periodic review and adjustment.

Annual Hiring Range: $55,000-$60,000 *Exempt (salaried) positions under FLSA are not eligible for overtime.

This position is funded by a grant, soft and/or restricted funds. Continued employment is contingent on the renewal of funding.

Essential Functions

Design and conduct research in evolutionary and population genomics analyses using large whole genome datasets

Analyze genomic datasets (inferring local ancestry, population structure, phylogenomics, patterns of hybridization), data interpretation, prepare manuscripts for peer-reviewed publications, and present research findings at scientific conferences and seminars.

Opportunities to mentor and/or train junior research team members, including undergraduate and graduate students in computational and genomic research methods.

Assist with coordination of permitting procedures and logistics of sample collection.

Contribute to a collaborative and supportive environment and ongoing research activities in the lab.

Required Qualifications and Skills

Ph.D. in evolutionary biology, genomics, ecology, genetics, or related field by the start date

Research background in population genomics, evolutionary genomics, conservation genomics, or related field

Knowledge of analyzing large-scale genomic datasets

Proficiency with computational and bioinformatic approaches for genomic data analysis, such as using R, slurm, on a Linux/Unix computing cluster

Knowledge of population genetic and evolutionary theory and its application to genomic data

Strong organizational and data-management skills

Excellent written and verbal communication skills, including ability to communicate research findings through scientific publications and presentations

Ability to work independently and collaboratively while contributing to a supportive, interactive research environment

Preferred Qualifications (optional)

Experience or interested in learning data analysis of degraded DNA genomic datasets from museum specimens, experience conducting analyses to study hybridization, introgression, and inferring demographic histories.

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