The Conservation Fund Freshwater Institute Research Fellow (Precision Aquaculture)

About the role

The Conservation Fund Freshwater Institute Research Fellow (Precision Aquaculture) will contribute to the USDA Agricultural Research Service (ARS) cooperative research project, "Innovating New Technologies that Improve Efficiencies of Recirculating Aquaculture Systems." This fellowship focuses 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).

Responsibilities

• Contribute to multidisciplinary research activities supporting the Precision Aquaculture initiative.
• 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.
• Enhance research skills through experimental design, data collection, analysis, and interpretation of results.
• Improve scientific communication abilities with technical reports, peer-reviewed publications, conference presentations, and collaborations with industry partners.

Requirements

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

• 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.
• Familiarity with land-based recirculating aquaculture systems.

Qualifications

• Master's Degree or Doctoral Degree received within the last 60 months.
• Citizenship: U.S. Citizen Only.

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.
• Familiarity with land-based recirculating aquaculture systems.

Benefits

The participant will receive a monthly stipend commensurate with educational level and experience. The anticipated stipend range is $75,000 to $82,000 annually.

Pay

The participant will receive a monthly stipend commensurate with educational level and experience. The anticipated stipend range is $75,000 to $82,000 annually.

Schedule

The appointment will initially be for one year but may be renewed upon recommendation of ARS and is contingent on the availability of funds.

Contact

Please visit our Program Website for additional questions about the application process. Questions can also be emailed to ORISE.ARS.Northeast@orau.org and include the reference code for this opportunity.