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Postdoctoral Associate – BioSciences
Job role insights
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Date posted
January 30, 2025
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Closing date
January 30, 2025
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Hiring location
Houston
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Offered salary
Competitive
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Qualification
Doctorate Degree
Description
Dr. Tom Miller's lab in the Department of BioSciences is looking to hire a Postdoctoral Research Associate in the field of Ecology. The successful candidate will be based in the Miller Lab and will collaborate with the research team from the Sevilleta Long-Term Ecological Research program (SEV-LTER) to model the dynamics of habitat ecotones in response to global change drivers using observational and experimental data from SEV-LTER. The ideal candidate will have training and interests at the interface of experimental and theoretical ecology, including strong quantitative and statistical skills. The position will primarily involve analysis of existing data, modeling, and manuscript preparation. There may be additional opportunities for field work at SEV-LTER depending on interest. The ideal candidate will have experience with (or openness to learning) data-driven demographic models (e.g., matrix or integral projection models) and spatial population-dynamic populations (e.g., reaction-diffusion or integro-difference equations).
The start date for this role is flexible and can be scheduled any time in 2025. If you have not yet received your PhD degree but expect to graduate by May or summer 2025, we welcome your application as well.
Working Conditions: This position may be funded by a grant, soft and/or restricted funds. Continued employment is contingent on the renewal of funding.
Required Qualifications
- Ph.D in Biology, Ecology and Evolutionary Biology, Environmental Science, or related disciplines
Required Skills
- Proficiency in R for purposes of data management, statistical analysis, and numerical simulation
- Excellent verbal and written communication skills, as well as oral presentation skills
- Organization and time management skills
- Knowledge of modern research methods, data collection, and analyses
- Knowledge of the principles and techniques of the subject discipline
- Ability to write scholarly papers based on ongoing research in order to submit them to journals for publication
- Able to work in a collaborative environment
- Able to work independently and professionally with minimal supervision and direction
Preferred Qualifications
- Experience with demographic models and/or spatial population-dynamic models
Essential Functions
- Construct and analyze ecotone models
- Documents, analyzes, and maintains research data
- Mentors, oversees, and/or trains junior research team members and students
- Collaborate with team members at other institutions
- Publishes and presents research findings
- Supports project management and collaboration across institutions or disciplines
- Performs all other duties as assigned
Skills
Overview
Rice University, located in Houston, Texas, is a renowned private research institution known for its diverse academic offerings. It consists of eight schools, each focusing on various fields of study, including humanities, social sciences, business, engineering, natural sciences, architecture, music, and continuing studies. Established in 1912, the university has a rich history, including its origins as the Rice Institute following the tragic murder of its benefactor, William Marsh Rice.
Rice is a highly regarded institution, classified as an "R1" university, signifying high research activity, and it has been a member of the Association of American Universities since 1985. Its academic prowess is reflected in its distinguished alumni, including Nobel laureates and prominent scholars such as Marshall, Rhodes, and Churchill Scholars.
Additionally, Rice's athletic teams, known as the Rice Owls, compete in NCAA Division I sports, representing the university in the American Athletic Conference. The university is also situated near major cultural and medical centers in Houston, adding to its appeal as a leading academic and research institution.
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Company size
Founded in
1912
Location
Houston
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