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Post Doc Associate

Cornell University
United States, New York, Ithaca
337 Pine Tree Road (Show on map)
Feb 22, 2025
Post Doc Associate

We are seeking a postdoctoral fellow to lead data integration and quantitative analyses for a project examining connections between human and environmental health around Lake Victoria, Kenya. The postdoctoral fellow will be based at Cornell University and will work primarily on a research project analyzing how cyanoHABs around Lake Victoria, Kenya are impacting aquatic food webs and human health risks. The work will require interdisciplinary approaches to integrate and analyze a multi-year dataset that includes both in-situ water quality monitoring data, fish sample analysis for nutrients and algal toxins, and household survey data. The additional integration of remote sensing data is also highly desirable.
The postdoctoral fellow will pursue established questions, and will also have considerable latitude to develop their own questions, as well as to contribute to group projects and global analyses. The fellow will be primarily supervised by Kathryn Fiorella and will also have close engagement with Peter McIntyre.
Our group's work uses a planetary health approach to integrating research on environmental change and human health. Lake Victoria is a dynamic system that has experienced substantial and sustained ecological and water quality change, and accompanying changes to the patterns of fishing, fish consumption, and livelihoods and offers a rich system for these questions. The position will build on the group's prior research in this setting and contribute to better understanding connections between human and environmental health, social-ecological systems, and planetary health alongside longstanding regional partner organizations in Kenya.

Qualifications:
* Expertise in a relevant discipline (e.g., epidemiology, ecology, nutrition, economics) with
PhD conferred by the start of the position
* Demonstrated expertise in organization and analysis of quantitative datasets and
statistical modeling in Stata or R
* Excellent written, verbal, and interpersonal communication skills
* Established record leading publications
* A collaborative approach and ability to work independently
* Experience with interdisciplinary methodologies and the integration of different data
sources is preferred
* Ability to work collaboratively and with culturally diverse and international colleagues

Position details:
We offer a competitive salary based on educational background and relevant experience. The
annual salary range would be $61,008-80,000. The position will be full-time with benefits,
including health insurance. The researcher is expected to be present in Ithaca, NY throughout the
contract and office space will be provided at Cornell University. Alternative arrangements may
be possible if there is an excellent fit with a researcher based elsewhere. The position is for one
year, with a possible extension contingent on funding availability.
Please apply through Academic Jobs Online at https://academicjobsonline.org/ajo/jobs/29771

Upload a single pdf file as LastName.pdf that includes:
* brief cover letter detailing the experience and skills you would bring to the position
* CV
* relevant publication or writing sample
* sample code that you wrote
* the names and contact information for three references
Applications will be reviewed starting immediately, with hiring to take place as soon as possible.
Ideally the candidate will begin the position in June 2025 or earlier, though the position start date
can be negotiated.

Pay Range:

$61,008.00 - $87,000.00

Pay Ranges:

The hiring rate of pay for the successful candidate will be determined considering the following criteria:

  • Prior relevant work or industry experience.
  • Education level to the extent education is relevant to the position.
  • Academic Discipline
  • Unique applicable skills.

Employment Assistance:

For general questions about the position or the application process, please contact the Recruiter listed in the job posting or email mycareer@cornell.edu.

If you require an accommodation for a disability in order to complete an employment application or to participate in the recruiting process, you are encouraged to contact Cornell University's Office of Institutional Equity and Title IX at voice (607) 255-2242, or email atequity@cornell.edu.

Applicants that do not have internet access are encouraged to visit your local library, or local Department of Labor. You may also request an appointment to use a dedicated workstation in the Office of Talent Attraction and Recruitment, at the Ithaca campus, by emailing mycareer@cornell.edu.

Notice to Applicants:

Please read the required Notice to Applicants statement by clicking here. This notice contains important information about applying for a position at Cornell as well as some of your rights and responsibilities as an applicant.

EEO Statement:

Diversity and Inclusion are a part of Cornell University's heritage. We are a recognized employer and educator valuing AA/EEO, and we do not tolerate discrimination based on any protected characteristic, including race, ethnic or national origin, citizenship and immigration status, color, sex/gender, pregnancy or pregnancy-related conditions, age, creed, religion, actual or perceived disability (including persons associated with such a person), arrest and/or conviction record, military or veteran status, sexual orientation, gender expression and/or identity, an individual's genetic information, domestic violence victim status, familial status, marital status, or any other characteristic protected by applicable federal, state, or local law. We also recognize a lawful preference in employment practices for Native Americans living on or near Indian reservations in accordance with applicable law.

Cornell University embraces diversity and seeks candidates who will contribute to a climate that supports students, faculty, and staff to all identities and backgrounds. We encourage individuals from underrepresented and/or marginalized identities to apply.

2025-02-21
Applied = 0

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