Design and execute computational models, including sequence analysis, protein modeling, and structural prediction.
Develop computational pipelines using Python, R, AlphaFold, machine learning, and bioinformatics tools.
Analyze wet lab data to generate predictive models that inform experimental design and project direction.
Create compelling visualizations, figures, and simulations for technical summaries and presentations.
Document modeling approaches, code, scripts, and datasets to ensure reproducibility.
Collaborate directly with the wet lab, human practices, and website teams to integrate and communicate computational findings.

Experience in Python, R, MATLAB, or similar programming languages is a strong asset.
Familiarity with bioinformatics tools, sequence databases, protein modeling algorithms, or structural prediction software is a strong asset.
Analytical skills with the ability to translate biological questions into computational workflows.
Good organization and documentation skills to ensure reproducible results.
Team-oriented and comfortable collaborating in interdisciplinary environments.
Interest in computational biology, synthetic biology, systems biology, molecular modeling, or algorithmic design.

Flexibility for hybrid work
Opportunity to develop skills in computational modeling, bioinformatics, and data analysis

Computational Biology Research Assistant

Key skills