Lood Van Niekerk
Senior Machine Learning Scientist I at Flagship Pioneering
Cambridge, Massachusetts, United States
Summary
👤
Senior🎓
Top SchoolLood Van Niekerk is a senior machine learning scientist with a decade of experience applying ML to biology and personalized health, currently leading biomolecular foundation model work as the first hire at a Flagship Pioneering startup. He brings a strong research-to-product track record from Harvard Medical School—where he co-developed ProteinGym and advanced sequence models for indels and disordered regions—and industry roles at Ginkgo Bioworks and LifeQ, including running a global $60k antibody developability competition. Educated at Oxford (MSc Computer Science, cum laude) and Stellenbosch (BSc Hons Data Science, cum laude), he blends rigorous academic methods with practical engineering to ship models across proteins, enzymes, DNA and RNA. Passionate about startups and business, he intentionally builds cross-disciplinary skills and plans to translate technical depth into venture leadership.
10 years of coding experience
6 years of employment as a software developer
MSc Computer Science (cum laude), MSc Computer Science (cum laude) at University of OxfordBSc (Hons) Computer Science (Cum Laude) Data Science, BSc (Hons) Computer Science (Cum Laude) Data Science at Stellenbosch UniversityBishops Diocesan CollegeSummer School Program Business in Europe, Summer School Program Business in Europe at EM Strasbourg Business School
English, Afrikaans, French
Stackoverflow
935reputation
31kreached
3answers
0questions
Github Skills (172)
transformers10
benchmark10
language-model10
python10
data-manipulation10
3d-structure10
protein-design10
deep-learning10
gpu10
computational-biology10
dataframes10
pandas10
editor10
controlling10
ml10
Programming languages (12)
Github contributions (5)
loodvn/EVE
May 2021 - Apr 2024
Official repository for the paper "Large-scale clinical interpretation of genetic variants using evolutionary data and deep learning". Joint collaboration between the Marks lab and the OATML group.
Contributions:195 pushes, 5 branches in 2 years 11 months
pytorchclinicaldeep-learninggeneticmarks
OATML-Markslab/EVE
Mar 2022 - Mar 2024
Official repository for the paper "Large-scale clinical interpretation of genetic variants using evolutionary data and deep learning". Joint collaboration between the Marks lab and the OATML group.
Contributions:3 PRs, 2 comments in 2 years
evolutionheuristicsclinicalcollaborationneuroevolution
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