プロフィール詳細

プロジェクトを作成

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Dr. Nikolai S.に依頼

Belgium

PhD | ML for Drug Discovery | Cheminformatics & Pharma Data Expert

プロフィール概要

I’m a PhD-level biomedical scientist with 5+ years of experience applying machine learning and cheminformatics to drug discovery. I’ve built ML models for molecular property prediction (e.g. binding affinity, ADMET, pKa), performed large-scale virtual screening, and developed 2D/3D QSAR and GNN models using PyTorch, RDKit, and Python. I also have a strong track record in scientific writing, pharma regulatory insights, and academic editing, supported by 3 master's degrees in Drug Development, Industrial Pharmacy, and Health Informatics. I'm here to help you with: ML/data analysis for drug discovery Scientific writing/editing and publication support Literature reviews and technical reports Cheminformatics, docking, and screening workflows Languages: English, Dutch, Spanish, Russian Let’s collaborate to bring your scientific project to life — on time, with clarity and technical rigor.

専門分野

• ★ Chemoinformatics
• ★ Data Analysis
• ★ Health Informatics
• ☆ Molecular Modeling
• ☆ Molecular Docking
• ☆ Computational Chemistry
• ☆ Computational Biology
• ☆ Biostatistics
• ☆ Computer Simulation/Computational Modeling
• ☆ Predictive Modeling & Analytics
• ☆ Data Processing
• ☆ Cluster Analysis
• ☆ Data Visualization
• ☆ Big Data Analytics
• ☆ Data Management
• ☆ Data Manipulation
• ☆ Machine Learning
• ☆ Data Mining
• ☆ Data Cleaning
• ☆ Neural Networks
• ☆ Artificial Intelligence
• ☆ Deep Learning
• ☆ Statistics
• ☆ Regression Analysis
• ☆ Multivariate Analysis
• ☆ Nonlinear Regression
• ☆ Bayesian Statistics
• ☆ Correlation Analysis
• ☆ Health Data Analysis
• ☆ Bioinformatics
• ☆ Structural Bioinformatics
• ☆ Python
• ☆ SQL
• ☆ Excel
• ☆ Tensorflow
• ☆ LaTex
• ☆ R
• ☆ Tableau
• ☆ Scikit-learn
• ☆ Markup Languages
• ☆ Drug Discovery
• ☆ Hit-to-Lead & Lead Optimization
• ☆ Structure-Activity Relationship (SAR) Studies
• ☆ Drug Development
• ☆ Drug-Drug Interactions
• ☆ Health Technology Assessment
• ☆ Technical & Scientific Writing
• ☆ SOP & Protocol Writing
• ☆ Science Communication

サービス

• Writing
• Research
• Consulting
• Data & AI

Writing Technical Writing

Research Scientific and Technical Research, Systematic Literature Review

Consulting Scientific and Technical Consulting

Data & AI Predictive Modeling, Image Analysis, Algorithm Design-ML, Data Visualization, Big Data Analytics, Data Mining, Data Cleaning, Data Processing, Data Insights

職務経験

Computational Chemist

Acellera Therapeutics

7月 2020 - 11月 2024

ML Researcher

Stockholm University

10月 2019 - 6月 2020

学歴

Computational Chemistry and Biomedicine

Universitat Pompeu Fabra

10月 2020 - 11月 2024

Health Informatics

Karolinska Institute Stockholm - Sweden

9月 2018 - 6月 2020

Industrial Pharmacy

Katholieke Universiteit Leuven

9月 2017 - 6月 2018

Drug Development

Katholieke Universiteit Leuven

9月 2015 - 6月 2017

Bachelor of Pharmaceutical Sciences (Hons)

Katholieke Universiteit Leuven

9月 2012 - 6月 2015

認定資格

• Data Analytics

  Google

  5月 2025 - 現在

出版物

JOURNAL ARTICLE

Nikolai Schapin, Maciej Majewski, Alejandro Varela-Rial, Carlos Arroniz, Gianni De Fabritiis (2023). Machine learning small molecule properties in drug discovery . Artificial Intelligence Chemistry.

Alejandro Varela-Rial and Iain Maryanow and Maciej Majewski and Stefan Doerr and Nikolai Schapin and Jos{\'{e}} Jim{\'{e}}nez-Luna and Gianni De Fabritiis(2022). PlayMolecule Glimpse: Understanding Protein–Ligand Property Predictions with Interpretable Neural Networks . Journal of Chemical Information and Modeling. 62. (2). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 225--231. American Chemical Society ({ACS})