Research Fellow in Precision Aquaculture

Under the guidance of a mentor at The Conservation Fund's Freshwater Institute, the Research Fellow will contribute to the USDA Agricultural Research Service (ARS) cooperative research project, “Innovating New Technologies that Improve Efficiencies of Recirculating Aquaculture Systems.” This fellowship will focus on investigating the use of multispectral and hyperspectral imaging, olfactory sensing, and artificial intelligence (AI) to monitor fish health and welfare in recirculating aquaculture systems (RAS). The Research Fellow will participate in the Precision Aquaculture initiative to gain skills and experiences assigned by the lead Research Scientist. Learning activities include integrating sensors and developing prototypes to collect multispectral, hyperspectral, and volatile-compound data in challenging aquaculture environments; helping to develop AI-driven data-processing pipelines for fish health and welfare monitoring; and supporting the development of decision-support tools and robotic solutions for RAS.

Learning Objectives:

• Gain experience participating in multidisciplinary research activities supporting the Precision Aquaculture initiative.
• Learn to develop, integrate, and validate sensor systems and prototype devices for imaging and chemical sensing applications in aquaculture.
• Build skills in artificial intelligence, machine learning, and computer vision by contributing to tools that monitor fish health and welfare.
• Strengthen research skills through experimental design, data collection, analysis, and interpretation of results.
• Enhance scientific communication abilities with technical reports, peer-reviewed publications, conference presentations, and collaborations with industry partners.

Anticipated Appointment Start Date: Flexible; ideally in September-November 2026.

Appointment Length: The appointment will initially be for one year, but may be renewed.

Level of Participation: The appointment is full-time.

Citizenship Requirements: This opportunity is available to U.S. citizens only.

Qualifications:

The qualified candidate must have received a master's or doctoral degree in one of the relevant fields: Agricultural and Biological Engineering, Computer Science, Data Science, Electrical Engineering, or a closely related field. The degree must have been received within the past five years.

Preferred skills:

• Experience in sensor integration and system development for imaging and chemical-sensing applications, preferably in agriculture, aquaculture, or related environmental systems.
• Strong background in computer vision and machine learning, including the development of AI-based data-processing pipelines for image and chemical-sensor data.
• Proficiency in scientific programming and data analytics with Python, OpenCV, and MATLAB, along with experience in deep learning frameworks such as TensorFlow, PyTorch, and Keras.
• Experience in statistical analysis and data interpretation using tools such as R or SAS.
• Strong communication and collaboration skills, with the ability to research effectively in multidisciplinary research environments alongside engineers, biologists, and industry partners.
• Hands-on experience with robotics, automation systems, or decision-support tools in real-world settings is preferred.
• Experience with multispectral and hyperspectral image analysis for agricultural or aquacultural applications.
• Familiarity with land-based recirculating aquaculture systems.

Participant Stipend: The participant will receive a monthly stipend commensurate with educational level and experience. The anticipated annual stipend range is $75,000 to $82,000. There is an additional supplement for health insurance costs, which can be obtained through the Oak Ridge Institute for Science and Education (ORISE).

ORISE Information: The fellowship program is administered by Oak Ridge Associated Universities (ORAU) through its contract with the U.S. Department of Energy (DOE) to manage the Oak Ridge Institute for Science and Education. The selected candidate will be required to complete an application through ORAU at a later date.