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Research Associate Resume

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Evanston, IL

SUMMARY

  • me is a Data scientist with a PhD degree in Chemical Engineering and academic research exp erience in modeling.
  • Through post - processing research data, me developed my enthusiasm for data science while learning Python on my own.
  • me delivered results and justified conclusions through careful acquisition and interpretation of teh data.
  • me is a detailed oriented person who pays attention to teh characteristics of teh data to gain insight. In past projects, me collaborated with interdisciplinary teams with great interpersonal skills.
  • me is eager to apply research skills, logical thinking, and modeling experience to solve complex predictive problems in data science.

TECHNICAL SKILLS

  • Machine Learning Python
  • (Sklearn, Pandas) Jupyter Notebooks SQL C/C++
  • Git
  • Matlab/Octave
  • Gnuplot
  • Linux
  • Spark/Hadoop
  • Django
  • Minitab

PROFESSIONAL EXPERIENCE

Research Associate

Confidential, Evanston, IL

Responsibilities:

  • Successfully captured product distribution for alkylation reactions on solid acid catalysts through microkinetic modeling and solving a system of ordinary differential equations.
  • Improved efficiency of teh optimization of model parameters by estimating initial values from thermodynamic properties of reactive species.
  • Debugged and improved in-house C/C++ code to reduce teh computation time by 30%.
  • Developed Python code to process simulated data to facilitate visualization and optimization.

Postdoctoral Research Associate

Confidential, Minneapolis, IL

Responsibilities:

  • Established a model to screen cation-exchanged zeolites for potential selective adsorbents for H 2 S from Claus process tail gas with cluster and periodic DFT calculations.
  • Identified descriptor for adsorption energies on zeolites to aid teh design for superior adsorbents for H 2 S by performing energy decomposition analysis.

Graduate Research

Confidential, Evanston, IL

Responsibilities:

  • Constructed a computationally efficient model to study deNO x reactions over BaNaY zeolites assess using hybrid quantum mechanical/molecular mechanical calculations.
  • Determined rate-determining step for teh deNO x reactions in teh gas phase with transition state theory and microkinetic modeling by calculating teh Gibbs free energy surface.
  • Administrated and coordinated a 32-node Linux computer cluster for parallel computing.

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