Description

Three postdoctoral positions at the King Abdullah University of Science and Technology (KAUST) under the mentorship of Prof. Jürgen Schmidhuber.This project, located at the intersection of Reinforcement Learning and Material Science, focuses on developing innovative solutions for the discovery of novel chemical materials for direct air capture (DAC) technologies. By joining our team, you will contribute to pioneering research with the potential to drive significant advancements in combating climate change and promoting sustainability.

• Collaborate with a dynamic team of international researchers and industry partners.
• Design, implement, and validate advanced reinforcement learning models.
• Utilize reinforcement learning and evolutionary algorithms to discover new chemical materials.
• Publish and present research findings at high-impact conferences.
• Engage in a supportive environment that fosters professional growth and development.

Qualifications

• A Ph.D. in Computer Science, Chemical Engineering, Materials Science, or a related field, with a strong focus on deep learning.
• Demonstrated experience with publications in top-tier journals and conferences.
• Proficiency in programming languages commonly used in deep learning such as Python and familiarity with frameworks like TensorFlow or PyTorch.
• A keen interest in impactful applied research.
• Experience in Reinforcement Learning or Evolutionary Algorithms.
• Background in Deep Learning for Chemistry (desirable but not essential).

Application Instructions

• Your Curriculum Vitae (CV).
• A brief statement of research interests, explaining why you are interested in this position.
• Contact information for three references.