Curriculum Vitae aka CV aka Resume
Egor Marin
Machine Learning Scientist @ ENPICOM B.V.; @marinegor at most of the platforms.
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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. And I can communicate with people.
Software skills & activities
Bag of words: python, numpy, sklearn, scipy, pytorch, pytest, docker, ansible, bash, Ubuntu, 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.
🍝 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 WebDAV, proxy & VPN servers, websites, wrote a python(pyo3)+Rust(pest) parser for crystallographic data.
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.
🧬+🥩 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.
💊 structure-based drug discovery: performed large-scale virtual screening campaign, created robust accelerated virtual screening approach, communicated with CROs, oversaw functional tests.
Career
I have been roughly 8 years in science, working with membrane proteins and their structure-function relationships: GPCRs, (microbal) rhodopsins, membrane transporters.
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: May 2024.