Postdoctoral Research Associate: AI, Spectroscopy, and Data Science for Agricultural, Food, and Sustainable Systems
The SAGE Lab is seeking a motivated Postdoctoral Research Associate to contribute to interdisciplinary research involving artificial intelligence, machine learning, intelligent sensing, and data-driven decision systems.
The successful candidate will primarily work on the development of statistical, machine-learning, and deep-learning methods for complex sensing and process datasets. Research may involve data from spectroscopy and hyperspectral imaging, RGB or thermal imaging, IoT sensors, remote sensing, environmental monitoring, laboratory or process systems, and other multimodal sensing platforms.
Potential Research Areas
Potential research topics include:
- Machine learning and deep learning for sensing and process data
- Uncertainty quantification and trustworthy AI
- Multimodal sensor and data fusion
- Statistical modeling of small, noisy, incomplete, or high-dimensional datasets
- Computer vision and spectral data analytics
- Transfer learning and domain adaptation
- Real-time and edge AI
- Optimization and decision-making under uncertainty
- Intelligent monitoring and adaptive control systems
- Agricultural and environmental data science
- Food quality, food safety, and process monitoring
- Biomass, bioenergy, and circular-economy applications
Spectroscopy and hyperspectral imaging are important tools used within the lab, but prior specialization in a particular spectroscopy platform is not required.
Required Qualifications
Applicants should have:
- A Ph.D. in engineering, computer science, data science, or a closely related discipline
- Strong experience in machine learning, statistical modeling, data analysis, or algorithm development
- Strong scientific programming skills in Python, MATLAB, R, or related platforms
- Experience working with imaging, sensor, process, remote-sensing, spectral, or other complex datasets
- Ability to conduct independent research and publish in peer-reviewed journals
- Strong scientific communication and collaborative skills
Experience with real-time, automated, edge, or deployment-oriented AI and sensing systems is particularly desirable.
Experience with spectroscopy, hyperspectral imaging, chemometrics, computer vision, IoT systems, uncertainty quantification, stochastic control, or related methods is welcome but not required across all areas.
We especially value candidates who can connect computational methods with the physical, biological, or engineered systems represented by the data, rather than treating modeling as an isolated computational exercise.
Responsibilities
The position will approximately consist of:
65% — Research and Technical Development
Develop AI, machine-learning, statistical, sensing, optimization, and decision-support methods; analyze complex datasets; contribute to experiments and system development; and translate methods toward practical implementation.
25% — Proposal Development, Scientific Writing, and Publications
Work closely with the PI on research concepts, preliminary studies, competitive proposals, manuscripts, and development of the lab's externally funded research portfolio.
10% — Collaboration, Mentoring, and Research Dissemination
Participate in SAGE Lab activities, collaborate with interdisciplinary research teams, mentor students, and contribute to presentations, conferences, reports, and other scholarly activities.
Who Should Apply?
We encourage applications from researchers with strong computational backgrounds who are interested in applying their expertise to real-world challenges in:
Agriculture • Food Systems • Environment • Biological Systems • Energy • Sustainable Materials • Circular Economy
You do not need to have worked in all of these application areas. We are particularly interested in candidates with strong methodological foundations who are motivated to learn new domains and work collaboratively with experimental and application-focused researchers.
How to Apply?
Interested candidates are encouraged to contact:
Dr. Sambandh Dhal
Assistant Professor
Department of Bioproducts and Biosystems Engineering
University of Minnesota
Please include:
- Curriculum Vitae
- Brief description of research interests
- Relevant publications or research projects
- A short description of how your background could contribute to the SAGE Lab
Formal application information will be posted when the position becomes available.