Machine Learning Specialist

Selvita

Kraków, Poland

We are seeking a skilled Machine Learning Specialist to join our dynamically growing multidisciplinary AI Drug Discovery Team. The successful candidate will work with the latest deep learning technology in a team of highly qualified specialists in the field of drug discovery.

Key Responsibilities

Design and implementation of state-of-the-art machine learning models to tackle complex challenges in the field of computational chemistry and bioinformatics;
Interact with other teams in Selvita to understand their workflows and where the introduction of artificial intelligence and automation would be helpful;
Keep up to date with the academic literature to find new models and procedures to apply to computational chemistry and bioinformatics;
Preparation and processing of data required for model training and validation;
Integrating trained artificial intelligence methods in existing workflows;
Develop new workflows that contribute to the projects by improving speed and accuracy;
Implement AI/ML models on high-performance computers with GPU acceleration.

Fields of applications:

ML powered high throughput virtual screening to assess compounds’ activity;
Creation of embeddings and explorable subspaces for molecules;
AI informed chemical space exploration;
Chemical reactions prediction and retrosynthesis;
Generative methods for drug design and optimization.

Your Background

Master/PhD degree, preferably in machine learning, statistics, computer science, cheminformatics, bioinformatics, computational chemistry, physics or a related discipline;
Very good knowledge of modern methods of machine learning, artificial intelligence and neural networks;
At least 3 years of practical experience building, training and validating machine learning models;
Advanced programming skills in Python (knowledge of other languages is appreciated);
Experience with GPU acceleration for AI;
Work in a Linux/Unix environment;
Fluent professional and scientific English.

Additional skills (optional):

Basic knowledge of organic chemistry or biology;
Basic knowledge of KNIME or other low-code protocols;
Experience with distributed computing, docker and kubernetes;
Research experience in structure- or ligand-based drug design, identification and characterization of biological targets.

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