Richard Tjörnhammar
Engineer at Swedish Post and Telecom Authority
Solna kommun, Sweden
Summary
👤
Senior🎓
Top SchoolRichard Tjörnhammar is an engineer with a PhD in Biological and Biomedical Physics and over a decade of experience applying quantitative methods to complex scientific and regulatory problems. He has transitioned from academic research—developing multivariate analytics, factor analysis methods and computational structural biophysics—to spectrum engineering at the Swedish Post and Telecom Authority, where he now performs coexistence analyses, link-budget calculations and international technical regulation work. Proficient in R, MATLAB, Python and SEAMCAT, he blends statistical mechanics, machine learning and simulation to produce evidence-based policy and technical deliverables for CEPT, ECC and ITU. His background in integrating multi-omics and clinical data for diabetes research gives him a rare combination of domain depth and data-science rigor. He publishes and shares tools (e.g., Impetuous and related GitHub projects) that reflect a focus on reproducible methods and optimal data representations. Colleagues value him for turning complex physics and biological questions into practical, regulatory-ready solutions.
11 years of coding experience
10 years of employment as a software developer
Chinese Language and Literature, Average: 90/100, Chinese Language and Literature, Average: 90/100 at Wuhan UniversityDoctor of Philosophy (PhD), Physics, Doctor of Philosophy (PhD), Physics at KTH Royal Institute of Technology
English, Chinese, Swedish, German
Github Skills (9)
linux10
statistical-learning10
nix9
nixos8
nixpkgs7
dynamics5
simulation5
python4
factor-analysis3
Programming languages (2)
Github contributions (5)
richardtjornhammar/richardtjornhammar.github.io
Nov 2020 - Jul 2025
Contributions:22 pushes, 1 branch in 4 years 8 months
richardtjornhammar/impetuous
Mar 2019 - Jan 2023
A Statistical Learning library for Humans
Contributions:16 releases, 599 commits, 705 pushes in 3 years 11 months
statistical-learning
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