Research Assistant Professor in the Department of Geography (Ref.: 537606)
We invite applications from highly motivated and accomplished researchers for a Research Assistant Professorship in the Department of Geography. This position is ideal for researchers who aim to develop an independent research programme at the intersection of Geospatial Artificial Intelligence, Remote Sensing, and Geospatial Data Science. The successful candidate will contribute to the development of intelligent models that learn from large-scale and heterogeneous geospatial data and support scientific discovery and real-world applications.
We now invite applications for the captioned post(s).
Duties and Responsibilities
- Develop deep learning methods for complex geospatial and environmental problems.
- Develop geospatial foundation models using large-scale and heterogeneous geospatial data, including satellite imagery, multi-sensor time series, geographic datasets, and global land-surface products.
- Design deep learning and multimodal models for long-term, multi-source remote sensing time series.
- Incorporate geographical knowledge, physical principles, and process-based constraints into deep learning models.
- Explore foundation models and deep learning for interdisciplinary applications in agriculture, environmental monitoring, disaster monitoring, and sustainable development.
- Lead independent research projects and supervise postgraduate students.
- Develop collaborations across geography, computer science, environmental science, and related disciplines.
- Secure external research funding.
- Publish original research articles in leading journals.
Requirements
- A Ph.D. in Geography, Remote Sensing, Geoinformatics, Computer Science, or a related field.
- At least two years of postdoctoral or equivalent research experience, with a strong record of peer-reviewed publications.
- Strong programming and computational skills in Python and deep learning frameworks such as PyTorch or TensorFlow.
- Experience working with large-scale geospatial or environmental datasets.
- Experience with deep learning methods for geospatial applications, including Transformer architectures, geospatial foundation models, self-supervised learning, and multitask learning.
- A strong interest in interdisciplinary research and the ability to connect methodological innovation with real-world geospatial and environmental applications.
- Proven ability to work independently and collaboratively.
What We Offer
The appointment will commence as soon as possible on a temporary basis for 1 year, with the possibility of renewal subject to satisfactory performance and funding availability. A highly competitive salary commensurate with qualifications and experience will be offered. Other benefits include annual leave, medical benefits and free access to on-campus gyms and libraries.
How to Apply
The University only accepts online application for the above post(s). Applicants should apply online at the University’s careers site (https://jobs.hku.hk) and upload an up-to-date C.V. Review of applications will start as soon as possible and continue until October 31, 2026, or until the posts are filled, whichever is earlier.
The University is an equal opportunities employer and is committed to equality, ethics, inclusivity, diversity and transparency.
