We provide IT Staff Augmentation Services!

Visiting Postdoctoral Researcher Resume

5.00/5 (Submit Your Rating)

Long Island, NY

TECHNICAL SKILLS

Programming: Python, C, C++, SQL, PostgreSQL, Scala

Distributed system: Kafka, Spark, Hadoop, AWS, HBase, Git

Python Data, ML libraries: Numpy, Pandas, NLTK, Scipy, Scikit - learn

Scientific tools: ROOT, GEANT, VisIt

PROFESSIONAL EXPERIENCE

Fellow

Confidential, New York

Responsibilities:

  • Developed a real-time data pipeline to process online auctions for commercial sites such as eBay using Spark Streaming on an AW S cluster.
  • Implemented data ingestion with Kafka messaging queues.
  • Developed a distributed and scalable database system using HBase and PostgreSQL.
  • Pipeline processed about 1 TB of data per day.

Visiting Postdoctoral Researcher

Confidential, Long Island, NY

Responsibilities:

  • Designed and built teh hadronic calorimeter detector for sPHENIX particle physics experiment.
  • Implemented a software framework in C/C++ to analyze teh experimental data with ROOT.
  • Developed a real-time online monitoring system in Python to monitor sensor data.
  • Built models using machine learning classification algorithms using Scikit-learn for particle species identification.

Postdoctoral Researcher

Confidential, Knoxville, TN

Responsibilities:

  • Utilized teh TITAN supercomputer to implement a computational hydro-dynamical model gluon-plasma evolution using GPUs.
  • Developed physics analysis framework in C/C++.
  • Developed Monte Carlo simulations using GEANT to correct bias in experimental setup.
  • Developed data visualization software using VisIt.

Graduate Student

Confidential, Atlanta, GA

Responsibilities:

  • Developed and maintained software in C/C++ for several detector subsystems in PHENIX particle physics experiment.
  • Processed petabytes-per-year scale dataset with 1000s of CPUs in parallel processing.
  • Developed a PHP web interface with PostgreSQL backend to store experimental data.
  • Received outstanding physics graduate student award for research.

We'd love your feedback!