Michael Jendrusch
Researcher at DKFZ German Cancer Research Center
Heidelberg, Baden-Württemberg, Germany
Summary
👤
Senior🎓
Top SchoolMichael Jendrusch is a researcher and machine learning engineer specializing in generative models for protein design, currently building a small ML-assisted protein design team at DKFZ. With a background spanning a PhD at EMBL, postdoctoral roles, and a decade of interdisciplinary experience, he bridges deep learning, synthetic biology, and high-throughput experimental validation. He develops open-source tools—most notably the efficient protein generative model "salad" (Nature paper and public code) and the composable design library flexcraft—to deliver reusable pipelines for binder design, affinity maturation, and protein stabilization. Equally comfortable in wet labs and compiler internals, he has contributed to systems-level projects like the Nim compiler while leading assay development and screening at scale. Based in Heidelberg, he combines rigorous math and molecular biology training with pragmatic software engineering to accelerate deployable protein design workflows.
10 years of coding experience
4 years of employment as a software developer
Master of Science - MS Molecular Biology, Master of Science - MS Molecular Biology at Heidelberg University
English, German, Polish, French
Github Skills (8)
macros10
compiler10
nim-lang10
compiler-compiler10
javascript9
metaprogramming8
lang8
testing7
Programming languages (5)
Github contributions (5)
nim-lang/Nim
Apr 2016 - Jan 2017
Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).
Role in this project:
Back-end Developer
Back-end DeveloperContributions:6 commits, 5 PRs, 27 comments in 9 months
Contributions summary:Michael primarily contributed to the Nim compiler's codebase. Their work includes implementing a `COMMA` macro for C++ template type generation, adding test cases, removing object field mangling for JavaScript, and improving JavaScript FFI. The changes involved modifications to the compiler's internal code generation, JavaScript code generation, and the addition of supporting test files. The user demonstrated familiarity with Nim's compiler internals and the integration of JavaScript functionality.
pythonnim-langelegancecompilerprogramming-language
mjendrusch/nimna
Jan 2017 - Mar 2018
Contributions:1 release, 72 commits, 58 pushes in 1 year 1 month
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