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Julia software developer, Bayesian inference researcher
I recently got my master in Physics at EPFL with a minor in Computational Science and Engineering and I just spent one year at Siemens working in MRI sequence programming. Now I am orientating myself into the machine learning field as I find it fascinating and promising! I have many interests in new technologies, computer programming, numerical simulations but also graphic design (web and print). I have been abroad a lot during my studies with one year at KTH (Stockholm) and a semester spent at the University of Edinburgh.
Technische Universität Berlin
Doctor of Philosophy - PhD, Artificial Intelligence
December 1, 2017 – July 1, 2022
The University of Edinburgh
Elementary Particle Physics
January 1, 2014 – January 1, 2014
EPFL
Minor, Computational Science & Engineering
January 1, 2013 – January 1, 2014
EPFL
Master's degree, Physics
January 1, 2012 – January 1, 2015
EPFL
Bachelor's degree, Physics
January 1, 2009 – January 1, 2012
PlantingSpace
Julia software developer, Bayesian inference researcher
April 1, 2022 – Present
Berlin Institute of Technology (Technische Universität Berlin)
Research Associate
December 1, 2017 – March 1, 2022
Berlin Metropolitan Area
Humboldt-Universität zu Berlin
Intern in Machine Learning
September 1, 2016 – September 1, 2017
Berlin Metropolitan Area
Siemens
Intern in MRI sequence programming
February 1, 2015 – February 1, 2016
Lausanne, Vaud, Switzerland
The University of Edinburgh
Teaching Assistant
September 1, 2014 – December 1, 2014
Greater Edinburgh Area
EPFL
Teaching Assistant
September 1, 2012 – June 1, 2014
Lancaster University
Intern in Particle Physics
July 1, 2012 – September 1, 2012
Cultural Fit Analysis
The candidate's academic and research background aligns well with a research-intensive culture. The diverse educational institutions (Edinburgh, EPFL, TU Berlin, Humboldt-Universität) suggest adaptability. However, the resume lacks explicit details on contributions to open-source projects, community involvement, or specific team-based project outcomes that would further demonstrate cultural fit beyond academic research.
Soft Skills & Operational Fit
The candidate's experience as a Teaching Assistant at multiple institutions suggests strong communication and mentoring skills. The research roles indicate an ability to work independently and solve complex problems. However, specific details on collaboration in team-based research projects are limited.