Assistant Professor in Analytics & Operations

Imperial College Business School is seeking qualified applicants for the position of tenure-track Assistant Professor in Analytics and Operations.

Imperial College London, one of the world’s most important centres for research and teaching in the Natural and Physical Sciences, Medicine, Engineering, and Business, seeks qualified applicants (PhD in Business, Management, Computer Science, Operations Research/Management, Statistics, Engineering; (degree to be obtained before September 2024) for a tenure-track faculty position at the tenure-track Assistant Professor level to join the Analytics & Operations group at the Imperial College Business School.

The candidate should demonstrate capability for high-quality innovative research in their area, a strong research agenda and pipeline, and a line of research relevant to Data Science, Business Analytics, Operations Research, Operations Management and/or Information Science/MIS. The successful candidate(s) will contribute to research, teaching and service at the Business School.

Research:
• To develop a broad range of research within Analytics & Operations, broadly defined
• To direct, lead, or contribute to, a research area at the highest scientifically rigorous levels, disseminating findings in peer reviewed journals, and through participation in national and international conferences
• To supervise, train and mentor research staff and students at the highest scientifically rigorous levels.
• To foster scientific collaborations through organising, attending and contributing to multidisciplinary meetings, within the Department and with other appropriate parties at Imperial.
• To attend and contribute to research and administrative meetings within the Department as and when requested.

Education - Teaching and Training:
• To teach and examine courses at all levels – undergraduate, masters and higher research degrees – through lectures, seminars, tutorials, course work and personal supervision.
• To plan and review own approach to teaching.
• To supervise PhD candidates.
• To provide pastoral support for students.
• To contribute to curriculum development at College and broader level

Strategy and Business Planning:
• To participate in the business planning and objective setting process for the academic team and the departments
• To make a significant contribution to building and establishing links between the appropriate departments and colleagues in other parts of the Business School and wider College.
• To play an active part in the strategic planning of financial, staff and research resources.
• To represent the Department, the Business School and College at external meetings, as appropriate.

Leadership and Team Working:
• To demonstrate excellent leadership skills regarding individual performance, academic teams, the department, the Business School, College, and when participating in national/international initiatives.
• To work collaboratively with all members of the multi-disciplinary team and the College as required.
• To resolve conflict and difficult situations through negotiation and discussion, involving appropriate parties.
• To adhere to College guidelines on leave including reporting absence.

• PhD in Business, Management, Computer Science, Operations Research/Management, Statistics, Engineering (degree to be obtained before September 2025)
• The candidate should demonstrate capability for high-quality innovative research in their area, a strong research agenda and pipeline, and a line of research relevant to Data Science, Business Analytics, Operations Research, Operations Management and/or Information Science/MIS.
• The ideal candidate would be experienced in teaching in areas relevant to the department.

Candidates who wish to obtain more information about the position and Imperial College Business School before applying can contact Gah-Yi Ban Interested candidates should apply online and send their CV along with the application form, cover letter, research statement, teaching statement and evidence of teaching scores (where applicable).

Interviews can start before the closing date.

Job closes 1st November 2024.

Hybrid working may be considered for this role. Staff working in roles that are suitable for hybrid working will normally be expected to work 60% of their time onsite. The opportunity for hybrid working will be discussed at interview.