PhD Psoition

Job Description

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PhD psoition

Khalifa University of Science and Technology

Khalifa University is home to the UAE’s leading research centers as interdisciplinary research units focused on long‑term strategic priorities addressing regional and global challenges in a systematic and targeted manner via engagement of world‑class researchers and facilities. These research centers are at the heart of KU’s global leadership in use‑inspired research.

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Abu Dhabi, United Arab Emirates

Academic

Earth Magnetism & Rock Physics (EMRP)

Energy, Resources and the Environment (ERE)

Seismology (SM)

Full time

Student / Graduate / Internship

2500 - 5000 € / Year, Salary amount depends on the quality of candidate's profile

Master

25 August 2026

13 August 2026

I am seeking a highly motivated PhD candidate to conduct interdisciplinary research at the interface of geophysics, rock physics, and remote sensing, with applications to critical mineral exploration, environmental studies, and energy resources.

The research will focus on developing and integrating geophysical, rock-physics, and remote-sensing AI- and physics-based approaches to better characterize the subsurface and understand the physical properties of geological materials.

• Critical mineral exploration and characterization, including identification of geological and geophysical signatures associated with mineralized systems;
• Environmental geophysics, including subsurface characterization, environmental monitoring, and assessment of geological and environmental processes;
• Energy-related applications, including characterization of conventional and renewable energy resources, geothermal systems, subsurface energy storage, and related geological settings;
• Regional seismic imaging interpretation;

The successful candidate should have a strong academic background in geophysics, applied geophysics, remote sensing, machine learning, or a closely related discipline. Experience with geophysical data processing and interpretation, remote-sensing techniques, GIS, and/or rock physics is highly desirable. Candidates with experience in programming and scientific computing (e.g., Python, MATLAB, or similar environments), quantitative data analysis, and integration of multidisciplinary Earth-science datasets are particularly encouraged to apply.