Doctoral student in Water Resources Engineering with a focus on radar remote sensing and AI

Description of the workplace

The current position will be placed in the Division of Water Resources Engineering, Department of Building and Environmental Technology. Here, research and teaching pursue the understanding of how water resides and is transported in nature and urban systems from an engineering perspective. This includes but is not limited to, comprehension and modeling of the components of the hydrological cycle as well as geospatial modeling of water quality and quantity in agricultural systems. At the division, there are about 35 employees and around 20 PhD students. The current position is within the Remote Sensing and AI in Hydrology research group.

The Department of Building and Environmental Technology has a stimulating and international environment consisting of PhD students, postdocs, and teachers from many parts of the world. Here, research and teaching take place in an open and progressive climate with challenges and collaborations both within academia and with industry partners, both nationally and internationally. The work environment is characterized by commitment, collaboration, creativity, and personal responsibility.

Subject description

The Remote Sensing and AI in Hydrology research group within the Division of Water Resources Engineering focuses on integrating various remote sensing (RS) techniques for measuring, i.e., land surface deformation, precipitation, etc., including both satellite-based and ground-based radar sensors. This Ph.D. project will investigate the interplay between rainfall (e.g., weather radar data), surface water management (e.g., dam operations, river diversions, and irrigation practices), and groundwater depletion and how these interactions contribute to ground subsidence. Using InSAR data, the study will map subsidence patterns in river basins globally, particularly in regions where surface water management practices significantly alter groundwater recharge. Artificial Intelligence (AI) models will be developed to analyze the relationship between surface water management policies, groundwater levels, and subsidence rates. The goal is to propose integrated water management strategies that minimize subsidence risks while ensuring sustainable water use. The outcome may include a global map of subsidence risks linked to surface water management, and RS-AI-based tools for monitoring and predicting subsidence and groundwater levels under different water management scenarios.

Work duties

The main duties of doctoral students are to devote themselves to their research studies, which includes participating in research projects and third-cycle courses. The work duties can also include teaching and other departmental duties(no more than 20%), such as

• organazing seminars
• activitites related to Ph.D. students such as organazing social events, field excursions, and departmental Ph.D. students meeting

Admission requirements

A person meets the general admission requirements for third-cycle courses and study programmes if the applicant:

• has been awarded a second-cycle qualification, or
• has satisfied the requirements for courses comprising at least 240 credits of which at least 60 credits were awarded in the second cycle, or
• has acquired substantially equivalent knowledge in some other way in Sweden or abroad.

A person meets the specific admission requirements for third cycle studies in Water Resources Engineering if the applicant has:

• At least 120 credits in subjects of relevance to the field of research, including at least 75 second-cycle credits in a relevant field for the subject area, or
• A second-cycle degree in Civil and Environmental Engineering, Water Engineering, or similar.

Additional requirements:

• Very good oral and written proficiency in English.
• Practical knowledge of analysis of remote sensing (RS) data, satellite image processing (radar data processing), google engine, or artificial intelligence in water-related subjects.
• Programming skills in MATLAB, Python, or similar

Assessment criteria

Selection for third-cycle studies is based on the student’s potential to profit from such studies. The assessment of potential is made primarily on the basis of academic results from the first and second cycle. Special attention is paid to the following:

Knowledge and skills relevant to the thesis project and the subject of study. An assessment of ability to work independently and to formulate and tackle research problems. Written and oral communication skills. Other experience relevant to the third-cycle studies, e.g. professional experience.

Other assessment criteria

Consideration will also be given to good collaborative skills, drive and independence, and how the applicant, through experience and skills, is deemed to have the abilities necessary for successfully completing the third cycle programme.

We offer

Lund University is a public authority, which means that employees get particular benefits, generous annual leave, and an advantageous occupational pension scheme. Read more on the University website about being a Lund University employee Work at Lund University. 

Terms of employment

Only those admitted to third-cycle studies may be appointed to a doctoral studentship. Third-cycle studies at LTH consist of full-time studies for 4 years. A doctoral studentship is a fixed-term employment of a maximum of 5 years (including 20% departmental duties). Doctoral studentships are regulated in the Higher Education Ordinance (1993:100), chapter 5, 1-7 §§.

How to apply

Applications shall be written in English and include a cover letter stating the reasons why you are interested in the position and in what way the research project corresponds to your interests and educational background. The application must also contain a CV, degree certificate or equivalent, and other documents you wish to be considered (grade transcripts, contact information for your references, letters of recommendation, etc.).

Welcome to apply!