05 ago - Italia
Cambrex
Cambrex Profarmaco Milano is looking for a curious and dynamic intern interesed in Artificial Intelligence.
For our Site in Paullo (Milan) we are looking for a trainee interested in with an expertise in ML methods and AI to insert in our Analytical Development team for an industrial secondment focused on building an AI-powered HPLC recommendation engine. This project leverages proprietary pharmaceutical data to develop machine learning models that predict optimal chromatographic conditions for new compounds.
- Responsibilities:
- Design and curate a structured experimental knowledge database linking molecular representations (SMILES, InChI, fingerprints), physicochemical descriptors, chromatographic method parameters, and experimental outcomes, with a focus on data quality, reproducibility, and design suitable for ML;
- Develop a feature selection pipeline for classical descriptors (RDKit, Mordred) and learned representations (molecular fingerprints, graph-based embeddings);
- Research, train, and benchmark predictive models for chromatographic outcomes (retention behaviour,
mobile phase strength, column selectivity class), exploring both interpretable models and state-of-the-art approaches;
- Design a molecular similarity module grounded in chemical space geometry, evaluating distance metrics and embedding spaces for nearest-neighbour method retrieval from historical data;
- Build a recommendation engine that unifies predictive modelling and the similarity module, with uncertainty quantification, confidence scoring, and explainability to support trust and adoption by domain scientists;
- Extend the engine into an agentic LLM interface that allows natural language interaction with the underlying models and database;
- Validate the system on held-out experimental data, document methodology to publication standard, and present research outputs to both technical and domain-expert audiences.
Qualifications and Skills:
- Degree in Computer Science/Engineering or a clos
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