Lab Engineer /Research Associate in Machine Learning for Chemistry

Poranne Lab, Schulich Faculty of Chemistry, Technion Israel Institute of Technology
Appointment: Full-time
Start date: Flexible (preferably by early 2026)
About the Lab:
The Poranne Group is a computational physical organic chemistry group that develops and applies machine learning methodologies to advance discovery and understanding in chemistry. Our research focuses on interpretable deep learning, molecular representations, and chemistry-aware models that connect data-driven insights with fundamental chemical understanding. The group operates at the interface of computational organic chemistry, machine/deep-learning, and data science. For more information, visit our website
Position Summary:
We are seeking a highly motivated Lab Engineer/Research Associate to take a leading role in our labs research activities. The successful candidate will be responsible for developing and applying machine learning models for molecular and physical systems and training graduate and undergraduate r

דרישות:

Essential qualifications:
M.Sc. or Ph.D. in Computer Science, Computational Chemistry, Bioinformatics, Physics, or a related field.
Strong proficiency in Python and key ML/scientific libraries (PyTorch, JAX, TensorFlow, NumPy, pandas, PyTorch Geometric, RDKit, etc.).
Solid understanding of software engineering best practices (version control, testing, packaging, CI/CD).
Experience with DevOps/MLOps tools (including Docker, Kubernetes, MLflow, DVC, etc.).
Demonstrated experience applying ML to scientific or engineering data (e.g., molecular simulations, protein structures, reaction networks, spectroscopy, materials data).
Comfortable working in Linux-based development environments and with cloud/HPC systems.
Preferred qualifications:
Experience with AI models for molecules or materials (e.g., graph neural networks, equivariant networks, molecular transformers).
Familiarity with scientific data formats and repositories (PDB, PubChem, ChEMBL).
Exposure to computational chemistry or structural biology workflows.
Contributions to open-source scientific software or AI toolkits.
Strong cross-disciplinary communication skills and intellectu