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Sambandh Dhal

1 week ago

PhD and Master's Research Positions in AI, Data Science, and Sustainable Agricultural Systems University of Minnesota Twin Cities in United States

Degree Level

Master's, PhD

Field of study

Computer Science

Funding

Available

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Country

United States

University

University of Minnesota Twin Cities

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Keywords

Computer Science
Data Science
Environmental Science
Agriculture
Electrical Engineering
Deep Learning
Biology
Remote Sensing
Decision Making
Spectroscopy
Artificial Intelligence
Time Series Analysis
Computer Vision
Sensor Technology
Uncertainty Analysis
Environmental Sustainability
Hyperspectral Imaging
Optimisation
Statistics
ML

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About this position

Sambandh Dhal, Tenure-Track Assistant Professor in the Department of Bioproducts and Biosystems Engineering at the University of Minnesota Twin Cities, is looking for motivated PhD and Master's students to join the SAGE Lab (Sensing, AI & Green Systems Engineering).

The lab works at the intersection of artificial intelligence, data science, sensing, and sustainable systems. Research interests include machine learning and deep learning, uncertainty-aware AI and uncertainty quantification, computer vision and multimodal data fusion, hyperspectral imaging, spectroscopy, remote sensing, time-series and sensor-data analytics, AI for agriculture/food/environmental/ecosystem applications, and decision-making and optimization under uncertainty.

Students with backgrounds in engineering, computer science, data science, agricultural/biological engineering, environmental science, or related quantitative fields are especially encouraged to apply. The opportunity is for graduate research at the University of Minnesota Twin Cities in the United States.

To apply, email your CV and a brief description of your research interests to [email protected]. No deadline was stated in the post.

Funding details

Available

What's required

Motivated PhD and Master's students are sought. Preferred backgrounds include engineering, computer science, data science, agricultural/biological engineering, environmental science, or related quantitative fields. Interest in applying computational methods to real-world sustainability challenges is emphasized. Students should be interested in AI, machine learning, sensing, and data-driven research.

How to apply

Email the supervisor with your CV and a brief description of your research interests. Mention your background and fit with the SAGE Lab research areas.

More information can be found here

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