[ES_JOBS_NET] PhD Student Position in Geospatial Machine Learning, Texas A&M University

[Leila Character]

Dr. Leila Character is seeking a creative problem solver PhD student to
join her lab at Texas A&M University, Department of Geography, starting in
Fall 2026.

The successful candidate will work on projects closely aligned with Dr.
Character's expertise, focusing on collection, manipulation, and
preprocessing of remotely sensed and training data to enable production of
new information; development and application of deep learning models for
object detection and segmentation using high-resolution remotely sensed
data; and geospatial and spatial statistical analyses. Potential research
areas include:



·       *Environmental Monitoring:* Advancing methods for the detection,
characterization, and modeling of natural and ecological phenomena with
applications in the identification of environmental features, assessment of
ecological health, and spatial characterization of terrestrial and marine
environments.



·       *Geospatial Intelligence: *Developing approaches for a diverse set
of problems related to automatic target recognition (ATR), including remote
sensing data collection, preprocessing, and fusion; machine learning model
development and implementation; and human-in-the-loop decision-making
systems.



·       *Archaeological Machine Learning*: Developing deep learning and
remote sensing approaches for the detection, mapping, and analysis of
archaeological and cultural heritage features in terrestrial and underwater
environments; integrating data from lidar, sonar, and other sensing
modalities to advance heritage preservation, landscape analysis, and
repatriation efforts.



The student's research will leverage diverse datasets and state-of-the-art
machine learning frameworks contributing to both theoretical advancements
and real-world problem-solving. There may also be a significant fieldwork
component for data collection and ground-truthing.

Required Qualifications:

• A Master's degree in Geography, Environmental Sciences, or a closely
related/relevant field.

• Demonstrated proficiency in Python programming for machine learning
(e.g., TensorFlow, Keras, PyTorch, Scikit-Learn).

• Strong skills in Geographic Information Systems (GIS) software (e.g.,
ArcGIS Pro, QGIS) and remote sensing data processing and analysis.

• Experience with and understanding of deep learning and other machine
learning algorithms for feature detection.

• Excellent analytical, problem-solving, and communication skills (written
and oral).

• A strong interest in interdisciplinary research and the application of
advanced geospatial techniques to complex real-world problems.



Interested candidates are strongly encouraged to review Professor
Character's CV and recent publications to understand the scope and nature
of the lab's research. To express interest, please send an email to
leilacharacter at tamu.edu with the subject line "PhD Application - Geospatial
Machine Learning" including:

1. Your Curriculum Vitae (CV).

2. A short statement of interest (a couple of paragraphs in the email)
outlining your research experience, your specific interests that align with
Professor Character's work, and your long-term academic and career goals.
Leila Character, PhD
Assistant Professor, Department of Geography
Texas A&M University
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <https://mailman.ucar.edu/pipermail/es_jobs_net/attachments/20250929/4dd0d3a7/attachment.htm>