Postdoctoral Associate
- Brooklyn, NY, United States
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Job details
- Education
- Doctoral degree
- Working hours
- 37.5 hours per week
- Posting language
- English
- Posted
Original job description
Postdoctoral Associate
ANNOUNCEMENT OF
PROFESSIONAL
VACANCY
Applications are invited for consideration to the following position
Department:
School of Public Health
Budget Title:
Postdoctoral Associate
Salary Range:
(Based Upon Experience)$70,000.00 - $75,000.00
Descriptive Title:Postdoctoral Associate
Full-time, Monday to Friday, 9:00am - 5:00pm, 37.5 hours per week.
Vacancy
26-30
Description of Duties:
This is a grant funded position. -Analyze genomic and transcriptomic data; perform quality control and statistical analyses. -Develop, document, and maintain reproducible workflows and organized research data. -Integrate genomic, immune-response, and ecological findings; develop research hypotheses. -Prepare manuscripts, figures, reports, and conference presentations. -Coordinate with collaborators and mentor trainees in analysis and reproducibility. -Contribute to limited molecular workflows supporting sequencing, with technical staff. Grant-supported research on Borrelia persistence in wild vertebrate host species, integrating evolutionary genomics, host responses, and ecological observations. Effort allocation: 45% analysis; 20% reproducible workflows/data management; 15% integration and hypotheses; 10% scientific writing/presentation; 5% collaboration/mentoring; 5% limited molecular support. Total: 100%.
Qualifications:
REQUIRED: Doctorate by start date in a relevant biological or quantitative field; sequencing-data analysis; R or Python; Linux/Bash; statistics, reproducible research, and High Performance Computing environments; scientific communication and collaboration. Prior infectious disease experience is desired but not required. A doctoral degree in evolutionary biology, ecology, genomics, bioinformatics, computational biology, microbiology, epidemiology, biostatistics, computer science, or a related biological or quantitative field, completed by the start date. Experience analyzing at least one type of high-throughput sequencing data. Proficiency in R or Python and working knowledge of command-line Linux/Bash. Experience with statistical analysis and documented, reproducible research. Experience with High Performance Computing environments. Ability to interpret biological results, communicate clearly in English, and work independently and collaboratively. Evidence of research communication appropriate to career stage, such as publications, preprints, presentations, technical reports, or public code. PREFERRED: Evolutionary/population genomics, transcriptomics, microbial genomics, data integration, version control or workflow tools, host-microbe biology, sequencing-support methods, or mentoring. No expectation of all listed skills. Experience in one or more of the following: - Population genomics, phylogenetics, molecular evolution, transcriptomics, microbial genomics, or integration of genomic and phenotypic data. - Version control or workflow tools. - Host-microbe interactions, reservoir-host ecology, Borrelia, or immunology. - Molecular methods supporting sequencing. - Mentoring trainees. These are additional strengths, not an expectation that candidates possess every skill.
Persons interested should mail their resume and a letter of introduction
Additional Information:Interested candidates should submit their letter of introduction and resume to: Sergios-Orestis Kolokotronis (SOK@downstate.edu)
Closing Date for Receipt of Applications: 11/29/26
The Research Foundation is committed to equal opportunity and non-discrimination in employment for all qualified persons without regard to race, color, religion, sex, gender identity or expression, transgender status, national origin, citizenship, age, creed, disability, veteran status, marital status, familial status, military status, domestic violence victim status, sexual orientation, genetic characteristics/genetic information, pregnancy-related conditions, reproductive health decisions, prior arrest or conviction records, or any other trait protected by federal, state, or local law.