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Requirements:
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 intellectual curiosity.
Experience mentoring students or coordinating research teams.
Interest or experience in scientific writing.
What We Offer:
The Schulich Faculty of Chemistry provides a vibrant and collaborative research community at one of Israels leading scientific institutions.
The Poranne Group offers access to state-of-the-art computational resources and a strong network of collaborations across chemistry, physics, and computer science. Our group provides a supportive and intellectually stimulating atmosphere, emphasizing creativity, rigor, and teamwork. In our group, you will enjoy the chance to shape next-generation tools to address problems at the intersection of AI, theory, and experiment, as well as the freedom to explore creative research directions aligned with the labs mission.
Salary will be commensurate with qualifications and experience, following Technion guidelines.
How to Apply
Interested candidates should submit the following materials to Prof. Renana Poranne:
A cover letter describing research interests, experience, and motivation.
Curriculum vitae (including publications).
Contact information for two or more references.
Applications will be reviewed on a rolling basis until the position is filled.
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Requirements:
An analytical mind - comfortable working with data, metrics, and A/B testing.
Creativity - the ability to generate fresh campaign ideas and compelling messaging.
Strong organizational skills and the ability to manage multiple campaigns simultaneously.
High level of English (written and verbal).
Availability to work on-site in Karmiel - full-time.
Familiarity with AI marketing/automation tools - an advantage.
Experience with email marketing, tracking, and analytics platforms - an advantage.
Experience in a high-volume, multi-market / multi-language environment - an advantage.
The position is open to women and men alike.
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