I am looking to fill multiple post-doc positions broadly in the area of machine learning application in catalysis, available immediately (8/19) and through the Fall. My group is highly collaborative, both within the group on projects, and with external research groups. Example projects include:

• combined catalyst mechanism studies and machine learning methods to search for ideal materials
• development of machine learning methods in catalysis (graph convolution methods, deep reinforcement learning)
• application of machine learning to the discovery of electrochemical or thermal catalyst surfaces
• electronic structure and modeling of complex materials (oxides, disordered, surfaces, etc)

Ideal candidates would have expertise in computational chemistry or catalysis (DFT) and expertise in python and HPC environments. Machine learning background (courses, familiarity with common packages such as tensorflow/pytorch/etc) would help but is not required. Strong communication skills (written and presentation) are very important. 

If interested, please email to [email protected]:

• a 1-page cover-letter describing your expertise, goals, and what skills are you looking to learn in your postdoc
• your CV
• 1-2 relevant research papers
• (ideally but not mandatory) a link to public code repository with a relevant project.

For more details about my group, please see http://ulissigroup.cheme.cmu.edu