- Agency
- University of Florida
- Location
- Vero Beach, Florida
- Job Category
- Post Doctoral Appointments
- Salary
- $50,000
- Start Date
- 02/16/2023
- Last Date to Apply
- 02/15/2023
- Website
- https://fmel.ifas.ufl.edu/
- Description
- Posting snapshot: Postdoctoral fellowship to lead geospatial ecology of invasive mosquito vectors and arboviruses in the Black Sea Region. Position Summary. Applicants are invited to apply for a postdoctoral fellowship at the Florida Medical Entomology Laboratory (FMEL) of the University of Florida in Vero Beach, Florida. This two-year position is part of a multidisciplinary international project investigating and building research capacity for invasive mosquito vectors and arboviruses in Georgia, Turkey, and Ukraine as part of a Defense Threat Reduction Act (DTRA) grant funded through the U.S. Department of Defense. Research responsibilities of the postdoctoral fellowship will include developing online materials and teaching in person workshops on species distribution modeling, mosquito trapping and identification techniques, and geospatial modelling of vectors and arboviruses. The incumbent will be expected to train and work at the FMEL in Vero Beach, FL with travel to Georgia and Turkey for project fieldwork, workshops, and trainings. Expectations The initial appointment is for one year, with annual renewal based on satisfactory performance. Expected salary is $50,000/year, fringe benefits, and a cost-of-living increase after one year. The position start date will begin in spring of 2023. Required Degree Doctorate - entomology, ecology, biology, biostatistics, geography, or related fields. Minimum Requirements • The candidate must have a Ph.D. in entomology, ecology, biology, biostatistics, geography, or related fields. • Experience in environmental spatial and/or spatiotemporal modeling is required, preferably as it relates to arbovirus systems. • The candidate must have demonstrated effective written and oral communication skills in science. • Demonstrated experience in species distribution models using Maxent and R statistical programing language (e.g., biomod2, ensemble modeling approaches) • Demonstrated experience in working with geographic information systems (GIS) and processing and preparing remotely sensed environmental variables (e.g., temperature, precipitation, NDVI, land cover classifications) for analyses • Experience in or willingness to teach workshops in international settings. • Demonstrated success working as part of a team. Aims and Preferred Qualifications The incumbent will therefore have preferred qualifications to accomplish the following: 1) develop online materials and teach in person workshops on species distribution modeling to project collaborators in Georgia and Turkey; 2) create species distribution models for medically important mosquito vectors and make predictions to unsampled locations; 3) develop training materials and teach in person workshops on mosquito trapping and identification of a limited number of medically important mosquito species to collaborators in Georgia, Turkey, and Ukraine. Additional desired qualifications include: • Machine learning/deep learning experience with environmental data sets desirable • Strong organizational and communication skills • Interest and experience with mentoring graduate students • Trapping and identifying mosquitoes or other medically relevant arthropods Professional Development Opportunities Opportunities to engage in professional development activities that will enhance their experience and better prepare them for careers in academia, government institutions, or industry. These opportunities include but are not limited to grant proposal writing, mentorship of graduate students, and science communication through direct interactions with international collaborators and stakeholders. Required Application Materials Candidates should submit a cover letter describing research experience and career goals and how they fit this position, a curriculum vitae, and names and contact information for three references to Lindsay Campbell (lcampbell2@ufl.edu). Special Instructions Review of applications will begin on February 15, 2023 and continue until the position is filled. We are striving continuously to build and sustain an equitable and inclusive environment. Applicants from underrepresented groups are encouraged to apply. The final candidate will be required to provide an official transcript to the hiring department upon hire. Degrees earned from an education institution outside of the United States are required to be evaluated by a professional credentialing service provider approved by National Association of Credential Evaluation Services (NACES), which can be found at http://www.naces.org/. The University of Florida is An Equal Employment Opportunity Institution dedicated to building broadly diverse and inclusive employees. Hiring is contingent upon eligibility to work in the US. Searches are conducted in accordance with Florida's Sunshine Law. Search Committee Lindsay P. Campbell (chair), PhD, FMEL, UF; lcampbell2@ufl.edu Nathan Burkett-Cadena, PhD, FMEL, UF; nburkettcadena@ufl.edu Barry Alto, PhD, FMEL, UF; bwalto@ufl.edu
- Qualifications
- Doctorate - entomology, ecology, biology, biostatistics, geography, or related fields. Minimum Requirements • The candidate must have a Ph.D. in entomology, ecology, biology, biostatistics, geography, or related fields. • Experience in environmental spatial and/or spatiotemporal modeling is required, preferably as it relates to arbovirus systems. • The candidate must have demonstrated effective written and oral communication skills in science. • Demonstrated experience in species distribution models using Maxent and R statistical programing language (e.g., biomod2, ensemble modeling approaches) • Demonstrated experience in working with geographic information systems (GIS) and processing and preparing remotely sensed environmental variables (e.g., temperature, precipitation, NDVI, land cover classifications) for analyses • Experience in or willingness to teach workshops in international settings. • Demonstrated success working as part of a team. Aims and Preferred Qualifications The incumbent will therefore have preferred qualifications to accomplish the following: 1) develop online materials and teach in person workshops on species distribution modeling to project collaborators in Georgia and Turkey; 2) create species distribution models for medically important mosquito vectors and make predictions to unsampled locations; 3) develop training materials and teach in person workshops on mosquito trapping and identification of a limited number of medically important mosquito species to collaborators in Georgia, Turkey, and Ukraine. Additional desired qualifications include: • Machine learning/deep learning experience with environmental data sets desirable • Strong organizational and communication skills • Interest and experience with mentoring graduate students • Trapping and identifying mosquitoes or other medically relevant arthropods
- Contact Person
- Lindsay Campbell
- Contact Phone
- 772-226-6666
- Contact eMail
- lcampbell2@ufl.edu
