PhD thesis at Institut Curie

overview of the thesis

30 January 2016

Skills

  • Machine learning
  • data visualization
  • R
  • public speaking
  • scientific writing
  • healthcare

Summary

  • title: Unsupervised deconvolution of cell and environment specific signals and thier interractions in biological samples
  • pushed the borders of knowledge in statistical modelling of multidimensional genetical data
  • used blind source separation methods, unsupervised machine learning
  • analysed big volume of data (>100 datasets, (~30 000 samples by ~20 000 genes))
  • applied data clustering and dimension reduction
  • worked with and publish open source code on git platforms and docker
  • developed an R package for transcriptomic data analysis
  • contributed > 3 to scientific publications as data analyst and 2 as a first author (publication list: https://orcid.org/0000-0002-5244-0708)
  • wrote scientific publications with LaTeX/.Rmd
  • worked in interdisciplinary team of 15 people
  • interacted with experimentalists (bench scientists, medical doctors) and theoreticians (mathematicians, IT, physicists)
  • won 2nd place of professional pitch competition, ABG
  • won 3rd place in scientific pitch competition
  • arrived 8th/208 in Capsim Simulation business competition as a part of a student team
  • delivered scientific presentations in front of >100 scientific experts
  • delivered pitches and presentations to general public (>1000 people)
  • created graphical supports with vector graphics
  • taught in Statistics, Informatics & Mathematics division at Pharma faculty
  • completed courses on: Big data, Machine Learning, Analytics, Communication, Certificate in Business & Administration: Business & Management & Strategy & Finance , Technologies & Public Policy
< Back
DeconICA