1. krynski.marcin@outlook.com
07754936870
SE8 5BN London, UK MARCIN KRYNSKI
I am a data scientist, recently awarded a PhD in physics.
I am a puzzle solver. I enjoy gathering evidence, finding
patterns, trying new methods, solving problems and
getting a bigger picture understanding of the situation.
Education
2010 - 2015 PhD in Physics, Warsaw University of
Technology. Thesis focused on quantum dynamics
simulations of Brownian-like oxide ions transport in solid
electrolytes; data analysis with use of machine learning
methods - passed with distinction. Awarded Rector’s Prize
for the Best Science Projects.
2005 - 2010 MSc in Physics, Warsaw University of
Technology. Thesis focused on fuzzy logic application in
data analysis.
Experience
Feb 2016 - now Software engineer in algorithm
development team in Geneity Ltd – Python, SQL, HTML,
Git.
Jan 2014 - Sep 2015 Fellow researcher at Faculty of
Physics, Warsaw University of Technology. Data analysis
based on machine learning methods (clustering, pattern
recognition).
May 2014 International collaboration with dr Issac
Abrahams, Queen Mary University of London:
modification of Reverse Monte Carlo method for solving
large-scale crystallographic structures.
March - May 2013 Internship at Department of Chemistry,
University of Oslo (data mining and analysis (neural
networks, genetic algorithms) of simulation data).
Oct 2012 Five-day neutron beam session at Rutherford
Appleton Laboratory (ISIS, Chilton, UK).
Oct 2008 - Aug 2009 One-year exchange at Technische
Universität München.
Feb – July 2009 Six-month internship at Max-Planck
Institute for Physics in Munich (developing automatic data
acquisition for the double beta decay experiment).
References
 Prof. Franciszek Krok – PhD supervisor
 Dr Isaac Abrahams – collaborative researcher
 Prof. Michalł Urbanski – MSc supervisor
Skills
 Proficient in developing and using machine learning
methods: decision tree, random forest, neural
networks, Bayesian networks, clustering, dimensionality
reduction (PCA), k-means, Monte Carlo, genetic
algorithms and many others.
 Proficient in Matlab coding, including CUDA parallel
computing technology and usage of Unix based
systems. Coding in C/C++ and Python.
 Ability to explain complex ideas to various audiences.
I published a children’s book about radioactivity and
radio isotopes.
 Exceptional communication and interpersonal skills –
five years as an active member of a research group,
teaching classes in physics (over 400h), two
international collaborations.
 Proficient in data analysis, data mining and data
presentation and visualization.
 Proficient in solving complex numerical problems using
advanced mathematical methods: Fourier analysis,
partial differential equations, finite element method,
fuzzy logic, Bader partitioning scheme and others.
 MSc finished with grade average 4.8/5 - advanced
university courses: probability theory, statistics
(including Bayesian), algebraic geometry, mathematical
analysis, and nonlinear dynamics.
 A team player. I was a co-investigator in a large grant
project – 11 scientists, 3 years, budget of £160 000,
where I developed theory complementing experiments.
 Very good organizational and time management skills.
I was the principal investigator of two grants: 12month
National Science Centre grant and a 4year super-
computer calculation grant. Both realized on schedule.
 Result-oriented approach. All major steps of research
were published in peer-reviewed journals, with impact
factor reaching 7.4 (first author in three of five
articles).
 Proficiency in result and results presentation – six oral
presentations and 4 posters at international scientific
conferences.
 Proficiency in Microsoft Word, PowerPoint and Excel.
 In my free time I compose music and play several
instruments, including guitar and violin.