Project Description:

Enzymes enable the synthesis of complex pharmaceutical agents because they catalyze selective chemical reactions under mild conditions. Sankar Research Lab develops and tests computational tools capable of proposing synthesis routes (or “recipes”) that primarily use enzyme catalysis to make complex pharmaceutical agents. These computational tools would identify ways to cost-efficiently manufacture complex target molecules and would improve our ability to synthesize a diverse library of complex chemical compounds for drug discovery programs.

The successful candidate will join multidisciplinary, highly collaborative research group to invent novel synthesis routes for producing medicines by applying innovative Artificial Intelligence (A.I.) algorithm(s) for decision making in enzymatic synthesis planning. Depending on candidate interests, the candidate will also have the opportunity to experimentally test the predictions by combining traditional chemical & biological engineering principles with modern protein purification and small molecule characterization techniques . In addition, you’ll have the opportunity to expand your knowledge and skills through collaborations with talented and dedicated colleagues while advancing your career.

Requirements:

Background in Chemical Engineering, Biological Engineering, Enzyme reaction chemistry, Computer Science, Computer Engineering, Electrical and Computer Engineering, and/or related fields.

Project Description:

The Laboratory of Renewable Resources Engineering (LORRE) and the Department of Agricultural and Biological Engineering at Purdue have long-lasting collaborations with top Brazilian Universities and researchers and have hosted over a dozen of visiting scholars in the last decade. We are looking forward to strengthening up this relationship with Brazilian institutions by hosting an undergraduate student to spend a semester in our laboratory to collaborate in our research applied to modelling for data analysis of biological engineering projects.

Applied bioengineering research generates a large amount of data every day that needs to be analyzed using Machine Learning tools in an effective and timely manner. One of the research areas of interest at LORRE is Health, in which mammalian cells are cultured both in 2D (flasks) and 3D (50 mL bioreactors), and tissues are used in pathogen infection studies and multi-drug resistance studies.
The scope of this project is using modelling to leverage experimental data analysis and assist in design of experiments. The undergraduate student selected to join our laboratory through the PONTES program will have the chance to learn the machine learning tools utilized by our research group and collaborate closely with Purdue graduate students and mentors. They will apply these tools in MatLab and/or Python to generate valuable data for our public health-related projects.

Requirements:

Chemical Engineering student, desired experience in Machine learning model development, training in data analysis and coursework in Modeling in Engineering and Biological Systems.