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Job advertisement Ph.D. position in coastal remote sensing

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European Geosciences Union

Ph.D. position in coastal remote sensing

Ph.D. position in coastal remote sensing


Department of Civil, Architectural, and Environmental Engineering at the University of Texas at Austin


Austin, Texas, United States of America


Relevant divisions
Hydrological Sciences (HS)
Natural Hazards (NH)
Ocean Sciences (OS)

Full time

Student / Graduate / Internship

The position will be funded on a combination of research and teaching assistantships, which include full tuition support, stipend, benefits, and travel support.

Preferred education

Application deadline
Open until the position is filled

11 October 2023

Job description

Ph.D. position in coastal remote sensing

  • Call for Ph.D. student applications: The Coastal Hazards Lab in the Department of Civil, Architectural, and Environmental Engineering at the University of Texas at Austin is excited to invite applications from outstanding candidates for a Ph.D. position in our research group. Join us in Fall 2024 and embark on a journey to explore the fascinating world of coastal hazards through the lenses of remote sensing and machine learning.
  • About Us: The Coastal Hazards Lab is dedicated to advancing knowledge in coastal engineering. Led by Dr. Jun-Whan Lee, our research combines numerical modeling, machine learning, and remote sensing techniques to build resilient and sustainable coastal communities. We are committed to fostering diversity and inclusion in STEM, and we encourage applications from individuals representing groups traditionally underrepresented in the field. To learn more about our lab and ongoing projects, visit our website:
  • Qualifications: We are seeking a highly motivated and talented candidate with a master’s degree in civil engineering, coastal engineering, ocean engineering, geoscience, computer science, or a closely related field at the start of the appointment.
  • Desired skills: (1) a solid theoretical background in fluid mechanics and coastal process, (2) experience in remote sensing data (drone, Landsat, InSAR, Google Earth, etc.), (3) strong programming skills (Python, MATLAB, etc.), (4) experience in machine learning (TensorFlow, PyTorch, etc.), (5) strong written and oral communication skills, and (6) an interest in interdisciplinary research.
  • Contact: Interested students are encouraged to email Dr. Jun-Whan Lee with the title “Prospective Ph.D. student” ( Please provide (1) a one-page cover letter (describing prior research experience, interests, and career goal), (2) a CV, and (3) unofficial transcript(s) in a single PDF file. If you do not wish to be considered for financial aid or have your funding or fellowship, please indicate it in the email. All emails will be reviewed on a rolling basis, and suitable candidates will be contacted for interviews via email. Please get in touch with Dr. Jun-Whan Lee through email if you have any specific questions about the position.

How to apply

Please visit the Graduate School website and submit your application by the deadline on December 15, 2023: