Morten Hjorth-jensen
Professor Of Physics at University of Oslo (UiO)
Oslo, Norway
Summary
👤
Senior🎓
Top SchoolMorten Hjorth-Jensen is a computational and theoretical physicist with over three decades of academic experience, currently a Professor of Physics at the University of Oslo and formerly a faculty member at Michigan State University. His work centers on quantum many-body theory, theoretical nuclear physics, and the intersection of computational methods with emerging fields like quantum computing and AI/ML. He combines deep analytic training (PhD from UiO) with extensive numerical expertise, developing scalable computational approaches to complex quantum systems. Morten’s career includes postdoctoral research at Nordita and the European Center for Theoretical Nuclear Physics, reflecting a strong international research network. Known for translating abstruse many-body problems into practical algorithms, he brings both foundational theory and modern computational practices to bear on open problems in physics. Based in Oslo, he continues to bridge academic research, mentoring, and computational tool development for the physics community.
11 years of coding experience
9 years of employment as a software developer
University of OsloNorwegian University of Science and Technology
Italian, English, German, Spanish, French, Norwegian
Github Skills (66)
fenics10
computational-physics10
python10
relevance10
regression10
mechanics10
deep-learning10
markov-chain10
simulations10
statistics10
machine-learning-algorithms10
quantum-computing10
quantum-mechanics10
dft10
index-html10
Programming languages (5)
Github contributions (5)
CompPhysics/MachineLearning
Sep 2017 - Dec 2022
Course on Machine Learning and Statistical data Analysis with book at https://compphysics.github.io/MachineLearning/doc/LectureNotes/_build/html/intro.html. Contains Linear and Logistic Regression, Neural Networks and Deep Learning methods, Decision Trees, Random forests, Boosting methods and other ensemble methods, support vector machines and central unsupervised learning algorithms.
Contributions:1932 commits, 5 PRs, 2252 pushes in 5 years 3 months
pythonensemblevectorensemble-methodsstatistical-data
ComputationalScienceUiO/CCAD
Nov 2017 - Mar 2021
This folder is a placeholder for long term strategic planning of several stages in research applications, with a common denominator Computing Across Disciplines (CAD)
Contributions:77 pushes, 1 branch in 3 years 3 months
pythoncadlong-termstageslong
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