Position description
This newly created position will have overall responsibility in identifying new digitization opportunities and developing machine learning algorithms to screen and/or synthetize new materials (i.e., CO2 capture and conversion materials) and optimize equipment and processes.
This role is focused on developing AI algorithms to screen TRL 1 classes of Metal Organic Frameworks (MOF), Covalent Organic Frameworks (COF) and catalysts, which will then be developed and scaled up to industrial materials.
Minimum requirements
- Ph.D. degree in chemical or mechanical engineering, chemistry, computer science, artificial intelligence, or robotics.
- More than seven years of work experience, preferably relevant to the areas of data science and statistics, machine learning, and programming.
- Conversant in programming, data analysis, and machine learning applications.
- Demonstrated experience or ability to identify gaps, challenges, and business opportunities relevant to digitalization and artificial intelligence in carbon management domains.
Duties & responsibilities
- Design and develop machine learning systems as an integral part of new technology development.
- Work with material scientists and chemists to develop next-generation CO2 capture substrates (sorbents and solvents) and CO2 conversion catalysts (thermo-, electro- and photo chemical).
- Work with material chemical, process and mechanical engineers to develop next-generation CO2 capture processes (sorbents and solvents) and CO2 conversion processes (thermo-, electro- and photochemical).
- Take responsibility for project planning, execution, implementation and data analysis phases.
- Work with scientists and engineering to ensure transfer/translation of simulation results in the tangible synthesis of materials and demonstration of processes.
- Liaise with scientists, technicians, and various stakeholders to ensure seamless integration with ongoing and future activities.
- Train junior Saudi engineers, while keeping abreast of engineering and scientific developments in digitalization and machine learning in the oil and gas industry in general, and carbon management in particular.
How to apply
If you believe you meet the requirements for this role, please contact us with your CV and state "AAS - [Job Title]" in the subject line.