Professor / Associate Professor, Data Science for Energy Engineering

Ref: 6494C

King Abdullah University of Science and Technology

Saudi Arabia

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Role Managed by:

Lucy Roper

Research Associate

t: +44 (0)20 3928 7358


Primary Practice Group: Higher Education and Research

Salary & Benefits: Highly Competitive

Closing Date: 19/06/2023

Formal Interview Date: July

Established in 2009, King Abdullah University of Science and Technology (KAUST) is a graduate private research university. KAUST is devoted to finding solutions for some of the most pressing scientific and technological challenges in the world as well as Saudi Arabia in the areas of food and health, water, energy, environment and the digital domain. KAUST is a curiosity-driven, interdisciplinary problem-solving environment, with state-of-the-art labs, distinguished faculty and talented students. Although a relatively new university, KAUST has already established itself as a global top 100 university (U.S. News & World Report), and consistently outperforms leading technical universities on a number of impact and citation metrics.

KAUST brings together the best minds from around the world to advance research. More than 120 different nationalities live, work and study on campus. KAUST is also a catalyst for innovation, economic development and social prosperity, with research resulting in novel patents and products, enterprising startups, regional and global initiatives, and collaboration with other academic institutions, industries and Saudi agencies.

The Physical Science and Engineering (PSE) Division offers seven academic programs, including Applied Physics, Chemical Engineering, Chemistry, Earth Science and Engineering, Energy Resources and Petroleum Engineering, Material Science and Engineering, and Mechanical Engineering. These disciplines provide the foundation for the Division's quest to address some of the major challenges that we face in the world today, including those related to energy and the environment. PSE Faculty are internationally renowned and at the forefront of their field.

KAUST is seeking candidates in the area of applying data science and applied mathematics towards designing advanced thermal energy systems and industrial processes.

The successful candidate will have a Ph.D. in Mechanical engineering, Chemical engineering, Applied Mathematics or similar, with expertise in one or more of the following areas:

Developing numerical methods for high-performance scientific computing,
Numerical linear algebra, fast algorithms, parallel computing, and machine learning with applications in complex non-linear dynamical engineering systems

Candidates with proven scholarship at the intersection of physical modeling with statistical inference will be given preference, including computation methodologies for uncertainty quantification, inverse problems, large-scale Bayesian computation, and optimal experimental design in complex physical systems.

The ideal candidate will have a good knowledge of how energy and industrial systems are likely to evolve and a good grasp of energy and industrial systems evolution and assessment. They will have a well-established network of collaborators and be familiar with software and approaches used in LCA and TEA assessment. The successful candidate will have a strong fit with activities ongoing in KAUST's CCRC, KCC, KSC, ANPERC, and others.

The successful candidate will be responsible for conducting cutting-edge research, teaching postgraduate courses (2 courses per academic year), and supervising Masters and PhD students.

They will be able to demonstrate achievements within a relevant context, and evidence behaviours in alignment with the mission and values of KAUST.

If you wish to discuss this role further in confidence, please contact Lucy Roper on or +44 (0)20 3928 7358.

The deadline for applications is Monday 19th June at midday (BST).

For a conversation in confidence, please contact Lucy Roper  on or +44 (0)20 3928 7358.

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