"Faculty Position in Artificial Intelligence and Chemistry"

Position Overview

We invite outstanding applicants whose research lies at the intersection of Artificial Intelligence and Chemistry. The successful candidate will develop a competitive research program, contribute to teaching at the undergraduate and graduate levels, and engage in collaborative projects with faculty, students, and industrial partners.

The scope of the position is intentionally broad and may include (but is not limited to):

• Machine learning for molecular and reaction property prediction
• AI-based reaction modeling and retrosynthetic analysis
• Data-driven approaches to spectroscopy and structural analysis
• Cheminformatics and chemical data mining
• Computational catalysis or process optimization
• AI applications in analytical, organic, inorganic, or physical chemistry
• Automation in chemical experimentation or chemical robotics

The selected candidate will be free to shape the balance between research, teaching, and collaborative innovation, based on their strengths and interests. During the selection process, applicants will be given the opportunity to express their preferred profile:

• Research-intensive: Focused on high-level research with light teaching duties
• Balanced: Combination of impactful research and active teaching
• Teaching-focused with applied research: Heavier involvement in curriculum development and hands-on educational innovation

Qualifications

Required:

• Ph.D. in Chemistry, Artificial Intelligence, Computer Science, Chemical Engineering, or a related field.
• Demonstrated ability to apply AI or machine learning tools to problems in chemistry.
• Strong publication record in reputable journals or conferences.
• Excellent written and oral communication skills in English.

Desirable:

• Postdoctoral or equivalent academic or industrial experience.
• Experience in handling chemical datasets and tools (e.g., RDKit, DeepChem, Gaussian, ORCA, ChemML).
• Knowledge of modern machine learning techniques (e.g., deep learning, graph neural networks, generative models).
• Interest in interdisciplinary research and/or real-world applications.

Responsibilities

• Develop and lead a research program at the AI–Chemistry interface.
• Teach courses related to chemistry, machine learning, or data-driven science.
• Supervise MSc and PhD students and contribute to curriculum development.
• Collaborate across departments and with external partners.
• Participate in the university’s broader mission of innovation and knowledge transfer.

Application Process

Candidates are invited to submit the following documents as a single PDF file:

• Cover Letter (including statement of motivation and preferred profile: research-intensive, balanced, or teaching-oriented)
• Curriculum Vitae (with list of publications)
• Research Statement (2–3 pages)
• Teaching Statement (1 page)
• Contact information for three referees (or letters of recommendation)