More about our group

Postdoctoral openings

In addition to rolling postdoctoral openings, our group presently is seeking new postdocs in the following target areas:

-Natural language processing and data mining in conjunction with machine learning for materials discovery.

-Software development for machine learning and simulation automation with application to multi-objective, data-driven materials optimization.

-Development of multi-level beyond-DFT theory with machine learning in high throughput simulation.

-Specific applications areas include metal organic frameworks and water oxidation catalysts. Candidates with expertise and interest in these areas are especially encouraged to apply.

Interested applicants should send to 1) a cover letter specifying their area of interest/purpose for applying, dates of availability for starting a position, and current employment status; 2) a C.V. with the names of at least two references.


Graduate students  must be admitted to MIT but can join our group from any department inside MIT once admitted. MIT ChemE, where we are located, carries out department-wide admissions and does not admit students based on the needs of an individual professor. We are also affiliated with CSBi, which maintains similar policies, and offers rotations. We anticipate having openings for 3 or more admitted MIT graduate students in Fall 2018 broadly in the areas of machine learning and automation for rational catalyst design, method development for transition metal chemistry, and enzyme modeling. We also have openings for the following specific funded collaborative research projects:

-Data mining and machine learning design of experiments for uncovering new metal-organic framework materials for selective, electronically-driven gas detection and/or separation. This DARPA award is led by the Kulik group but involves a tight collaboration with the Smith group at MIT ChemE for new materials synthesis.

-Machine learning experimental and computational data sets to design new metal-organic framework materials for catalysis. This is a collaborative multi-PI DOE EFRC grant with strong experiment-theory collaboration led by the University of Minnesota.

-Multi-scale simulation of confined solutions: effect of pore chemistry and size on separations, dynamics, and phase transitions. This collaborative multi-PI DOE EFRC grant is an integrated experiment-theory collaboration led by MIT.

Feel free to email for more details.


We are always eager to welcome interested MIT undergraduate students to our lab.

Feel free to email for more details.

About Us

The Kulik group focuses on the development and application of new electronic structure methods and atomistic simulations tools in the broad area of catalysis.

Our Interests

We are interested in transition metal chemistry, with applications from biological systems (i.e. enzymes) to nonbiological applications in surface science and molecular catalysis.

Our Focus

A key focus of our group is to understand mechanistic features of complex catalysts and to facilitate and develop tools for computationally driven design.

Contact Us

Questions or comments? Let us know! Contact Dr. Kulik: