Disease Programmer - Researcher Lead

Overview

We are seeking a computational biology programmer (Researcher Lead) to develop user-friendly software tools for decision makers working in One Health, with a particular emphasis on African Swine Fever virus (ASFv) surveillance data.

In previous work, USDA-APHIS-NWRC developed the SQUEAL (Spatial QUantitative Evaluation for ASFv eLimination) model — a spatial disease transmission model for ASF in feral swine on real landscapes, with functions for evaluating control and surveillance strategies following Red Book policy. This model can be used to evaluate potential introduction scenarios and address uncertainties regarding best practices for resource deployment and rapid elimination.

However, the model is currently custom coded and requires specialized programming expertise to operate.

The successful candidate should be capable of building software and developing computer algorithms that use disease monitoring data to predict epidemiological outcomes, while creating workflows and interfaces that are accessible to managers and other non-technical users. The position requires substantial demonstrated database management capabilities, a strong working knowledge of wildlife health surveillance in the United States, and topic‑specific expertise related to feral swine ecology and ASFv.

This position will focus on transferring the SQUEAL model to a plug‑and‑play interface in which users can input scenario information through a graphical user interface (GUI) and automatically visualize outputs of interest. Improving accessibility of the model is critical for efficiently addressing the numerous uncertainties associated with ASFv readiness and response planning.

The programmer will work with a national team of federal and academic scientists, managers, and national program coordinators to continue development of the Feral swine Assessment and Response Management System (FARMS).

• linkage to Veterinary Services animal health emergency reporting workflows;
• WS lab messaging integration;
• automation of WS field data collection inputs into FARMS;
• development of data structures for WS disease surveillance data from feral swine;
• interactive visualization of surveillance data directly from the database;
• development of tools providing guidance for ongoing surveillance;
• development of mapping tools that support adaptive control area zoning and resource management during ASF response efforts.

The incumbent will also contribute to transferring the SQUEAL model for use within the FARMS platform, including design of interfaces for user inputs and output visualizations.

• presenting results to non-technical stakeholders;
• developing user manuals and supporting documentation;
• conducting all phases of software development with minimal oversight;
• describing software tools and analytical workflows in peer-reviewed publications or technical reports.

• Masters Degree in a related field plus five years of related experience or an equivalent combination of education & experience.
• Must be capable of building software and developing computer algorithms that use disease monitoring data to predict epidemiological outcomes, while creating workflows and interfaces that are accessible to managers and other non-technical users.
• The position requires substantial demonstrated database management capabilities, a strong working knowledge of wildlife health surveillance in the United States, and topic-specific expertise related to feral swine ecology and ASFv.
• Proficiency with using a computer programming language to automate data reporting.
• Experience creating web-based dashboards that summarize patterns in data and allow users to download data files.
• Knowledge of disease surveillance data derived from multiple diagnostic tests, including understanding the types of inference supported by different data streams.
• Experience designing and implementing interactive software that allows non-technical users to explore how parameter values affect processes of interest (e.g., an R Shiny app or similar platform for exploring disease surveillance design or risk assessment scenarios).
• Experience packaging scientific analyses into shareable software capable of making inferences from user-defined disease surveillance data (e.g., development of an R package for risk assessment).
• Knowledge of African Swine Fever virus surveillance protocols in the United States.
• Knowledge of feral swine ecology and management in the United States.
• Strong capacity to collaborate closely with USDA-APHIS-NWRC and VS personnel.

• Past experience working for, or in close collaboration with, USDA-APHIS-NWRC or USDA-APHIS-Veterinary Services.

Commensurate With Experience Plus Excellent Benefits

Employees work indoors and are protected from weather and/or contaminants, but not necessarily occasional temperature changes. The employee is regularly required to sit and often uses repetitive hand motions.