The Role
This is a full-time, permanent position at the Staff Engineer level in supporting KAUST Catalysis Platform research activities. The position requires a strong background in reaction engineering, the ability to work independently, as well as hands-on knowledge/experience with high-tech equipment, which are critical and necessary to enable state-of-the-art research.
Responsibilities
- Design, establish, and maintain specialized catalytic reactors (e.g., high-throughput, automatic platforms, photo, micro, electro, and transport reactors), including the development of control and safety protocols
- Lead or contribute to the enhancement of technical methodologies through the improvement of existing systems or the development of new approaches; extend technologies to new application areas and play a key role in intellectual development activities
- Oversee daily operation and maintenance of specialized reactors
- Coordinate with technical teams and specialists both on-site and off-site, locally and internationally
- Develop experimental protocols and analytical methodologies tailored to specific research needs
- Participate in Factory Acceptance Tests (FAT), Site Acceptance Tests (SAT), and on- and off-site training for selected equipment
- Train new users, including Master\'s students, PhD students, and postdoctoral fellows, on reactor operation and safety
- Develop and implement preventive maintenance plans for all assigned equipment, ensuring accurate and complete records of operation and maintenance
- Monitor equipment availability and utilization; order necessary spare parts and consumables for routine operations
- Collaborate with lab team members to provide general technical support to researchers
- Assist researchers in troubleshooting and resolving issues related to catalyst testing and equipment performance
- Provide comprehensive technical support to the Platform team as needed
- Develop and integrate machine learning models and programming tools to enhance interaction with high-throughput systems and automated platforms, enabling predictive maintenance, data-driven optimization, and autonomous experimentation
- Assist the Lab Manager in maintaining research equipment, scheduling preventive maintenance, and procuring supplies to ensure smooth and uninterrupted operations
- Provide daily support to users, offering both technical and scientific guidance
- Promote awareness of safety, hazard prevention, and occupational health issues; support the implementation and maintenance of effective safety protocols to ensure the safe operation of facilities
Qualifications
- PhD in Chemical Engineering, Catalysis, or a closely related field, with significant hands-on experience in the required area of specialization
- Minimum of five (2) years of post-PhD experience in catalyst testing, experimental systems, or related fields within academia or industry
- Familiarity with the structure and operational needs of university-based scientific research environments and graduate-level education
- Excellent verbal and written communication skills in English, with the ability to document, present, and explain technical information effectively
- Experience working on industry-linked projects, with a clear understanding of applied research, deliverables, and collaboration with external stakeholders
Required Skills
- Proven ability to work independently with strong problem-solving skills, while maintaining effective communication with faculty and the Lab Manager
- Reliable and experienced in performing both routine and non-routine equipment maintenance
- Demonstrated ability to work collaboratively and contribute to a cooperative, team-oriented work environment
- Background in chemical engineering and catalysis, with hands-on experience in prototype development and programming for experimental systems and automation
- Experience working with high-throughput (HT) reactors and automated platforms for catalyst testing and screening
- Proficiency in analytical techniques such as chromatography and spectroscopy, with the ability to interpret experimental data accurately
Preferred Skills
- Experience in machine learning and data analysis
- Familiarity with safety protocols and hazard prevention in laboratory settings