Staff Engineer – Industrial Catalysis Process Control

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

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