Peter Bremen

Background

About Peter Bremen

Qualifications: 1) Six years of postdoctoral experience in data analysis and computational modeling of large-scale, multidimensional neurophysiological data, interpreting results, forming conclusions, and determining future hypothesis-driven experiments 2) Six years of postdoctoral experience in data science techniques, e.g. artificial neuronal networks, Bayesian statistics, clustering, current-source density analysis, de-noising, digital filtering, principal component analysis, time-series analysis 3) Six years of postdoctoral experience in qualitative and quantitative psychophysical research methods, e.g. Likert-type scales, N-alternative forced choice paradigms, staircase methods, regression analysis, Bayesian statistics for modeling, electro-magnetic and video eye-tracking methods 4) Programming languages: Matlab (13 years), C/C++(4 years), Igor Pro (2 years), R (self-taught), Python (self-taught), hardware programming (Tucker Davis, NI, Arduino) 5) Published a total of 16 (7 first-author) papers in peer-reviewed scientific journals 6) Experienced in scientific and grant writing (2 postdoctoral fellowships awarded) 7) Gave invited talks at 3 international (USA) and 5 national (The Netherlands) conferences (2007 to 2015) and presented 20 posters at international conferences (USA) 8) Co-supervision of 3 Ph.D.(2 partial), 3 master, and 7 bachelor students 9) Initiated 2 local collaborations (Irvine, USA) resulting in 1 scientific paper and 4 conference poster presentations