Digested version of announcement of Zintellect code USDA-ARS-P-2024-0157
POSITION
Title: Disease modeler
Type: Full-time, 1-year term with possibility for renewal depending on performance
Duty station: NWRC, Fort Collins
Salary: $62,107-$74,361
Closing date: Open until filled, applications reviewed on an ongoing basis

We are looking for a disease modeler to develop spatial models of foreign animal disease transmission in free-ranging animal populations – especially on foot-and-mouth disease and African swine fever transmission in wild pigs and at the wild pig-livestock interface. Key objectives are to identify effective surveillance designs for early detection and response management and spatial control strategies to inform preparedness and response. This is an excellent opportunity to develop analytic tools that will be used to inform animal disease management, develop communication skills with a variety of stakeholders in multiple USDA agencies, and build interdisciplinary scientific networks. The Fellow will work with an interdisciplinary team of applied researchers and policy developers bridging disciplines such as disease modeling, statistics, epidemiology, genetics, livestock systems, disease control policy, and wildlife management. The position is located in Fort Collins, CO at the National Wildlife Research Center of USDA-APHIS-Wildlife Services within a team of statisticians and disease modelers focused on management applications in a variety of host-pathogen systems. The candidate will be co-mentored by scientists at USDA’s National Bio and Agro-defense Facility (NBAF) with opportunity to visit and spend time at NBAF.

DUTIES
Develop spatial models of disease transmission and algorithms for surveillance and control optimization.
Analyze simulation data using appropriate statistical techniques.
Locate and assimilate appropriate data from primary literature and experts to inform model parameters.
Estimate epidemiological parameters from field data.
Create and maintain computer code in a commonly used programming language.
Develop functions and/or packages that can be transferred readily for use by others.
Develop user-friendly applications for visualization of results.
Apply methods for open-source code sharing on platforms such as GitHub to allow co-development and accessibility.
Publish articles in peer-reviewed journals.
Give oral presentations at scientific conferences.
Prepare high-level reports and oral presentation of results for policy makers and funders.
Coordinate analysis and reporting among research and stakeholder partners.

REQUIREMENTS
Must be a USA citizen.

Must be proficient at:
Applying modeling techniques and procedures.
Developing algorithms to predict disease transmission dynamics.
Analyzing data using probability statistics and other appropriate techniques.
Designing and performing computer simulations.
Generating de novo or modifying established modeling methods.
Coding in a programming language (e.g., R, Matlab, C++, Python, or similar).

Must have:
Strong expertise in quantitative ecology/disease ecology/epidemiology.
Demonstrated research competency in the fields of applied statistics, computational biology, disease ecology, and/or spatial ecology.
Ability to understand and address a variety of research needs and program priorities related to control of wildlife or livestock disease management.
Ability to effectively and efficiently communicate technical information both orally (at conferences, workshops, and meetings with stakeholders) and in writing (for peer-reviewed publications) at all levels and be able to communicate their meaning to diverse audiences.
Ability to effectively coordinate and promote program activities to stakeholders and external audiences.

ADDITIONAL PREFERRED QUALIFICATIONS
Proficiency with extracting and manipulating geographical information systems (GIS) and global positioning system (GPS) data.
Knowledge of control methodologies that are used for disease in wildlife species, livestock, and at the wildlife-livestock interface.
Experience with implementing optimization techniques.

QUESTIONS and HOW TO APPLY
Apply here: Zintellect - Climb Higher (https://www.zintellect.com/Opportunity
/Details/USDA-ARS-P-2024-0157)
Please send any questions to: kim.m.pepin@usda.gov.