Duties

• Develop ways to detect Fusarium mycotoxigenic fungi and assess the potential impact of new and emerging Fusarium-induced crop diseases.
• Apply knowledge and skills to develop Machine Learning (ML)/Deep Learning models and algorithms on Next-Generation Sequencing (NGS) datasets including genomic, transcriptomic and metabolomic data.
• Analyze multi-omic data to assess impact of a Fusarium-induced crop diseases and mycotoxin contamination and to identify strategies to mitigate these agricultural problems.

Requirements

Conditions of Employment

• Males born after 12/31/1959 must be Selective Service registered or exempt.
• Subject to satisfactory adjudication of background investigation and/or fingerprint check.
• Direct Deposit: Per Public Law 104-134 all Federal employees are required to have federal payments made by direct deposit to their financial institution.
• Successfully pass the E-Verify employment verification check. To learn more about E-Verify, including your rights and responsibilities, visit E-Verify at https://www.e-verify.gov/
• Appropriations Law and Immigration Law requirements must be met.

Qualifications

This position requires a recent Ph.D. in computational/bioinformatics biology, genetics, plant biology, plant pathology, genomics, computer science or data science with a focus on Machine Learning (ML) or a related field of study that has equipped the applicant with the necessary knowledge, skills and abilities to perform the duties and responsibilities of the position.

Experience leveraging novel data types to address biological hypotheses through statistical inference with ML approaches is helpful. An optimal research approach would benefit from proficiency in programming languages Python, Bash, R, SAS, Perl, SQL and UNIX shell scripting and experience using data science tools such as pandas, tidyverse, NumPy, SciPy, Scikit-learn, H2O and Jupyter. In addition, the project goals would benefit from knowledge of deep learning frameworks for neural network inference in Python (TensorFlow, Keras, PyTorch, and Theano) and experience with statistical modeling and inference using large, biological datasets and NGS. This position requires experience using Linux and Windows.

Applicants must meet basic Office of Personnel Management (OPM) Qualification Standard's requirements for at least one of the scientific disciplines (noted below) necessary to perform the duties and responsibilities of the position.

General Natural Resources Management and Biological Sciences Series, 0401:
A. Degree: biological sciences, agriculture, natural resource management, chemistry, or related disciplines appropriate to the position.
OR
B. Combination of education and experience: Courses equivalent to a major, as shown in A above, plus appropriate experience or additional education.

Genetics Series, 0440:
Degree: genetics; or one of the basic biological sciences that included at least 9 semester hours in genetics.

Education

This position has a positive education requirement. You must submit a copy of your academic transcripts OR a list of college courses with credit hours, dates completed, and grades received to verify education when applying for this position. If this information is not provided, your education may not be appropriately evaluated and you may lose consideration for this position. If you are selected for this position, you will have to provide an official copy of your transcripts prior to entering on duty. Application materials will not be returned.

A Ph.D. is required that was obtained within the last four years.

Additional information

** ANNOUNCEMENT IS OPEN UNTIL FILLED OR MARCH 3, 2023**

The selectee is not required to report to a government office, however, the option to work in the Peoria, Illinois office may be available.

This position may also be eligible for flexible work arrangements as determined by agency policy and any applicable collective bargaining agreements.