Postdoctoral Research Associate: AI, Data Science, and Sensing Agricultural, Food, and Sustainable
Listed on 2026-10-05
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Research/Development
Data Scientist, Research Scientist
Key Responsibilities
The SAGE Lab (Sensing, AI & Green Systems Engineering) in the Department of Bioproducts and Biosystems Engineering at the University of Minnesota Twin Cities is seeking a full-time Postdoctoral Research Associate.
The SAGE Lab develops trustworthy, data-driven methods that connect sensing, artificial intelligence, and decision-making for agricultural, food, biological, energy, environmental, and materials systems.
Our methodological focus includes statistical and machine-learning, deep-learning, chemometrics, multimodal data fusion, computer vision, uncertainty-aware modeling, stochastic control, optimization, and deployable edge-to-cloud decision systems.
Spectroscopy, hyperspectral imaging, remote sensing, IoT, and process measurements are important data sources within this broader framework rather than requirements defining a single experimental profile. Candidates with strong computational backgrounds who are interested in learning new sensing technologies or application domains are encouraged to apply.
The SAGE Lab (Sensing, AI & Green Systems Engineering) in the Department of Bioproducts and Biosystems Engineering at the University of Minnesota Twin Cities is seeking a full-time Postdoctoral Research Associate.
The SAGE Lab develops trustworthy, data-driven methods that connect sensing, artificial intelligence, and decision-making for agricultural, food, biological, energy, environmental, and materials systems.
Our methodological focus includes statistical and machine-learning, deep-learning, chemometrics, multimodal data fusion, computer vision, uncertainty-aware modeling, stochastic control, optimization, and deployable edge-to-cloud decision systems.
Spectroscopy, hyperspectral imaging, remote sensing, IoT, and process measurements are important data sources within this broader framework rather than requirements defining a single experimental profile. Candidates with strong computational backgrounds who are interested in learning new sensing technologies or application domains are encouraged to apply.
Research and Technical Development – 65%- Develop and apply statistical, machine-learning, deep-learning, and decision-oriented methods for complex scientific and engineering datasets.
- Develop models for classification, regression, anomaly detection, forecasting, process monitoring, and control.
- Integrate multimodal data from imaging, spectroscopy, IoT sensors, remote sensing, environmental measurements, and process systems.
- Develop robust methods for small, noisy, incomplete, heterogeneous, or high-dimensional datasets.
- Evaluate uncertainty, calibration, generalization, transfer learning, domain adaptation, and sensor fusion.
- Develop stochastic-control, optimization, and decision-making approaches for systems operating under uncertainty.
- Build reproducible, deployment-oriented workflows for real-time, automated, edge, and cloud-based applications.
- Contribute to experimental design, data acquisition, sensor integration, or laboratory/field validation depending on project needs and background.
- Lead and co-author peer-reviewed scientific manuscripts.
- Work closely with the PI to strengthen the SAGE Lab's externally funded research portfolio.
- Identify and evaluate federal, state, foundation, and industry funding opportunities.
- Develop research concepts, hypotheses, objectives, and technical approaches.
- Contribute to computational and experimental plans, milestones, timelines, and deliverables.
- Generate and analyze preliminary data.
- Prepare figures, schematics, tables, and technical materials.
- Draft and revise technical sections of competitive grant and contract proposals.
- Lead and co-author peer-reviewed publications.
- Participate actively in SAGE Lab and departmental activities.
- Collaborate with faculty, interdisciplinary research teams, and external partners.
- Mentor undergraduate and graduate researchers.
- Contribute to technical reports, invention disclosures, conference abstracts, presentations, seminars, and professional meetings.
- Ph.D. in engineering, computer science, or a closely related discipline.
- Research experience developing and applying statistical, machine-learning, deep-learning, chemo metric, or related computational methods to imaging, spectral, sensor, process, environmental, or other complex scientific data.
- Strong quantitative data-analysis and…
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