Egor Marin

Machine Learning Scientist @ ENPICOM B.V.; @marinegor at most of the platforms.

Socials

• email: [email protected]
• github
• twitter
• linkedin
• bluesky
• google scholar
• ORCID

Profile

I have formal education in applied mathematics and physics, supplied with 1 year of full-time extracurricular education in computer science, and 7 years of computational lab experience.

I enjoy writing code, and want to write code that gets to run many times, and hence should be written wisely. Know biology, especially structural biology and common experimental and computational methods around it. Love open-source, do self-hosting since recently. Can communicate with people when I’m not sick.

Software skills & activities

Bag of words: python, numpy/sklearn/pytorch/lightning, polars🫶, huggingface🤗, uv/ruff❤️‍🔥, pytest, docker/compose, bash, mlflow, Ubuntu/nixos, HPC, SLURM.

💾 administrated ~15 Linux workstations and servers with ~40 users, managind ~200 Tb of research data.

😎 participated in Google Summer of Code contributing to MDAnalysis: introduced process-based parallelization to the library (see main PR).

🧑‍💻 contributed to opensource: reciprocalspaceship: wrote parser for serial crystallography data into binary dataframe-like class, ntfy-cryosparc: wrote web-server to parse CryoSPARC (tm) notifications and notify appropriate users.

🤓 MDAnalysis Core Developer since February 2025. For MDAnalysis, wrote a parallel backend for all analysis classes (dask/multiprocessing), added a DSSP module for native secondary structure assignment, currently working on an MMCIF parser.

🍝 performed large-scale calculations on SLURM and PBS, wrote bash scripts for reliable and reproducible data processing of serial crystallography data.

🏆 participated in data science competitions (top-10% in Kaggle “Predict Molecular Properties”, top-1 in first round of “Learning How To Smell”, top-10% in Takeda Signate competition, 5th place in Tochka Bank graph ML competition).

🤷‍♂️ self-hosted bunch of things: *arr, telegram bots, WebDAV, proxy & VPN servers, paperless, openwebui, you name it

🦀 Wrote a python(pyo3)+Rust(pest) parser for crystallographic data, contributed to polars-distance

Science skills & acitivities

Bag of words: structural biology, crystallography, cryoEM, cheminformatics, computer vision, data science, molecular docking, drug discovery, protein structure, GPCRs, membrane proteins, structure-based drug discovery, antibodies, protein language models, discrete diffusion, flow matching, AlphaOpenfold

🧬+🥩 structural biology: co-published papers in Science, Nature Communications, JACS, Science Advances, Journal of Chemical Information and Modelling, Scientific Data. Performed data analysis, wrote texts, created figures, managed writing process – the normal stuff.

💊 structure-based drug discovery: performed large-scale virtual screening campaign, created robust accelerated virtual screening approach, communicated with CROs, oversaw functional tests.

🤖 machine learning: did many ad-hoc ML applications in computer vision (background removal with NMF decomposition), clustering, supervised learning. Always try linear regression first, have a paper about it.

👾 deep learning: know about protein language models and their properties, AlphaOpenfold-like models and their applications, wrote toy discrete diffusion models, adapted open-source discrete diffusion models for other domains.

Career

I have been roughly 8 years in science, working with membrane proteins and their structure-function relationships: GPCRs, (microbal) rhodopsins, membrane transporters. Don’t work in academia anymore, while still doing some research.

Have mainly worked at the Moscow Institute of Physics and Technology, and got my PhD from the University of Groningen. Also, I have worked at many synchrotrons and XFELs, and also was a visiting research assistant at the University of Southern California.

Machine Learning Scientist

2024-current

Doing machine learning in biotech-oriented SaaS company.

Scientist

2017-2023

• conducted research, managed data, wrote publications, participated in conferences
• managed students (BSs & MSc diploma), created a course on modern protein crystallography

Scientific Journalist

2016-2017

• analyzed publicational activity of MIPT
• wrote press-releases on published papers
• communicated with scientists & media.

Education

Moscow Institute of Physics and Technology, 2013-2017 BSc in applied mathematics and physics, summa cum laude

Moscow Institute of Physics and Technology, 2017-2019 MSc in applied mathematics and physics, with specialization in biophysics and structural biology

Computer Science Center, 2020-2022 Full-time extracurricular education in computer science: Python, C++, Algorithms and Data Structures, Data Science, Intro to Linux Systems, Rust

University of Groningen, 2019-2023 PhD, diploma on “On the methods of studying protein-ligand interaction dynamics”

Last updated: February 2025.