Post-Doctoral Associate

About the Job

This position is 100% time for a one-year initial appointment, with the possibility of extension based on satisfactory performance and continued funding.

Please note, this position is not eligible for visa sponsorship including H-1B or Green Card sponsorship.

This position will provide scientific and technical support for Dr. Sambandh Dhals SAGE Lab (Sensing, AI & Green Systems Engineering) in the Department of Bioproducts and Biosystems Engineering at the University of Minnesota. 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. The labs core 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. The successful candidate will primarily advance data analysis, algorithm development, modeling, and translation of complex measurements into practical decision-support, process-optimization, and adaptive-control tools, while working closely with experimental and domain collaborators as needed. Candidates with strong computational backgrounds who are interested in learning new sensing or application domains are encouraged to apply.

Duties/Responsibilities

• 65% Research and technical development. The primary focus of this postdoctoral associate will be the development and application of data-science, statistical, machine-learning, deep-learning, and decision-oriented methods for complex scientific and engineering datasets. Major tasks may include developing models for classification, regression, anomaly detection, forecasting, process monitoring, and control; integrating multimodal data from imaging, spectroscopy, IoT sensors, remote sensing, environmental measurements, and process systems; developing robust methods for small, noisy, incomplete, heterogeneous, or high-dimensional datasets; evaluating uncertainty, calibration, generalization, transfer learning, domain adaptation, and sensor fusion; developing stochastic-control, optimization, or decision-making approaches for systems operating under uncertainty; and building reproducible, deployment-oriented workflows for real-time, automated, edge, or cloud-based applications. Depending on project needs and the candidates background, the postdoctoral associate may also contribute to experimental design, data acquisition, sensor integration, or laboratory/field validation, either directly or in close collaboration with experimental researchers. The candidate will be expected to ensure that modeling assumptions and outputs remain grounded in the constraints and behavior of the systems being studied and will lead and co-author peer-reviewed manuscripts arising from these research activities.
• 25% Proposal development, scientific writing, and publication. The postdoctoral associate will work closely with the PI to strengthen the SAGE Labs externally funded research portfolio and publication record. Responsibilities may include identifying and evaluating federal, state, foundation, and industry funding opportunities; conducting targeted literature and programmatic reviews; developing research concepts, hypotheses, specific aims, objectives, and technical approaches; contributing to experimental and computational plans, work packages, milestones, timelines, and deliverables; generating and analyzing preliminary data; preparing figures, schematics, tables, and supporting technical materials; and drafting and revising technical sections of competitive grant and contract proposals. The postdoctoral associate will also lead and co-author peer-reviewed manuscripts and may help coordinate inputs from collaborators and external partners. Strong scientific writing is expected; prior grant-writing experience is highly desirable but not required.
• 10% Lab participation, collaboration, mentoring, and research dissemination. The postdoctoral associate will be an active member of the SAGE Lab, participate in lab and departmental activities as appropriate, collaborate with faculty and external partners, and contribute to mentoring graduate and undergraduate researchers. Responsibilities may also include technical reports, invention disclosures, conference abstracts, presentations, seminars, and professional meetings. The successful candidate will be expected to contribute ideas, take ownership of assigned research problems, communicate effectively across disciplines, and support a collaborative and inclusive research environment.

Qualifications

Required

• Ph.D. in engineering, computer science, or a closely related discipline.
• Research experience developing and applying statistical, machine-learning, deep-learning, chemometric, or related computational methods to imaging, spectral, sensor, process, environmental, or other complex scientific data.
• Strong quantitative data-analysis and scientific-programming skills using Python, MATLAB, R, or an equivalent platform, including experience developing reproducible computational workflows.
• Demonstrated ability to conduct independent research, formulate data-driven research questions, evaluate models rigorously, and communicate results through scientific writing and presentations.
• Demonstrated ability to connect data analysis and modeling assumptions to the physical, biological, or process systems that generate the data, including an understanding of measurement limitations, system constraints, and realistic operating conditions. Direct hands-on experimental experience is welcome but is not required for all applicants.
• Excellent oral and written scientific communication skills, including the ability to contribute effectively to manuscripts, technical documents, and research proposals and to work in an interdisciplinary and collaborative research environment.
• Willingness to learn new computational, sensing, experimental, and proposal-development methods and to contribute intellectually to new research directions within the SAGE Lab.

Preferred

• Experience with multimodal sensing, computer vision, time-series analysis, uncertainty quantification, model calibration, transfer learning, domain adaptation, stochastic control, optimization, decision-making under uncertainty, or machine learning for small, noisy, incomplete, or high-dimensional datasets.
• Experience developing real-time, automated, edge, or deployment-oriented analytics, sensing, or decision systems that translate model outputs into practical actions or process decisions.
• Experience analyzing data from spectroscopy, hyperspectral or multispectral imaging, RGB/thermal imaging, IoT sensors, remote sensing, process instrumentation, or related measurement platforms. Hands-on experience with these instruments is beneficial but not required.
• Experience working with data from agricultural, food, biological, environmental, biomass/bioenergy, circular-economy, materials, or related sustainable systems, or demonstrated ability to transfer computational methods across application domains.
• Experience contributing substantively to competitive research proposals or grant applications, including technical writing, concept development, or preparation of proposal figures and supporting materials.
• Experience publishing peer-reviewed scientific manuscripts and mentoring undergraduate or graduate researchers.

Pay and Benefits

Pay Range: $62,232 - $70,000; depending on education/qualifications/experience

Please visit the Benefits for Postdoctoral Candidates website for more information regarding benefit eligibility.

• Competitive wages, paid holidays, and generous time off
• Continuous learning opportunities through professional training
• Medical, dental, and pharmacy plans
• Healthcare and dependent care flexible spending accounts
• University HSA contributions
• Disability and life insurance
• Employee wellbeing program
• Financial counseling services
• Employee Assistance Program with eight sessions of counseling at no cost

How To Apply

Applications must be submitted online. To be considered for this position, please click the Apply button and follow the instructions. You will be given the opportunity to complete an online application for the position and attach a cover letter and resume.

Additional documents may be attached after application by accessing your "My Job Applications" page and uploading documents in the "My Cover Letters and Attachments" section.

To request an accommodation during the application process, please e-mail jobcentr@umn.edu.

Diversity

The University recognizes and values the importance of diversity and inclusion in enriching the employment experience of its employees and in supporting the academic mission. The University is committed to attracting and retaining employees with varying identities and backgrounds.

The University of Minnesota provides equal access to and opportunity in its programs, facilities, and employment without regard to race, color, creed, religion, national origin, gender, age, marital status, disability, public assistance status, veteran status, sexual orientation, gender identity, or gender expression. To learn more about diversity at the U: http://diversity.umn.edu

Employment Requirements

Any offer of employment is contingent upon the successful completion of a background check. Our presumption is that prospective employees are eligible to work here. Criminal convictions do not automatically disqualify finalists from employment.

About University of Minnesota

The University of Minnesota, Twin Cities (UMTC)

The University of Minnesota, Twin Cities (UMTC), is among the largest public research universities in the country, offering undergraduate, graduate, and professional students a multitude of opportunities for study and research. Located at the heart of one of the nations most vibrant, diverse metropolitan communities, students on the campuses in Minneapolis and St. Paul benefit from extensive partnerships with world-renowned health centers, international corporations, government agencies, and arts, nonprofit, and public service organizations.

At the University of Minnesota, we are proud to be recognized by Forbes as a Best Employer for Company Culture (2026), Best Employer for Women (2023, 2025, 2026), and Best Employer by State (2022-2026). In 2026, we also received Culture Excellence & Industry Awards recognition for employee appreciation and work-life flexibility.