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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # VIE Data Scientist spécialisé en chimie - **Company:** UCB - **Location:** Eigenbrakel, Belgium - **Contract:** Temporary contract - **Skills:** Artificial Intelligence, Computer Programming, Databases, Data Cleansing, Experimental Data, Python (Programming Language), Laboratory Information Management Systems, Machine Learning, NumPy, Data Processing, Pandas, Matplotlib, Information Technology, Data Analytics, Feature Extraction - **Published:** June 17, 2026 - **Apply:** https://be.indeed.com/viewjob?jk=cf5cdd1eb9b517c2 ## About the Role Do you have experience in Python?, Do you have a Master's degree?, Master's degree or early-stage PhD in: * + Chemistry (organic chemistry, medicinal chemistry, materials science, etc.) + Cheminformatics + Data science applied to chemistry Or a hybrid background (chemistry / computer science / data science) Languages: Professional level of English required Technical Skills: * + Solid understanding of synthetic chemistry and chemical reactions + Experience or strong interest in data handling (data cleaning, structuring, curation) and experimental data analysis + Programming skills, ideally in Python (pandas, numpy, matplotlib, optionally RDKit) Interest or basic knowledge in: * + Machine Learning / Data Science + Cheminformatics and structure-based search ## Description UCB is an international biopharmaceutical company primarily engaged in the research, development, and commercialization of pharmaceutical and biotechnological products. It specializes in researching therapeutic solutions for patients suffering from severe diseases, treated by specialists, particularly in the fields of the central nervous system (including epilepsy) and inflammation (including allergies). The Braine-l'Alleud site specializes in chemical synthesis, development, manufacturing, and packaging of pharmaceutical products. More information at: www.ucb.com Overall Mission As part of a VIE program, the successful candidate will join an R&D/Discovery team to contribute to the valorization of more than 15 years of historical chemical reaction data. This mission is positioned at the intersection of synthetic chemistry, data science, and R&D digitalization, with a direct impact on future laboratory practices. Phase 1 - Data Structuring and Quality The initial objective will be to transform a large corpus of heterogeneous data into a reliable, consistent, and exploitable dataset. The VIE will be responsible for: * Cleaning, curating, and harmonizing datasets (formats, units, nomenclature, missing fields, inconsistencies) * Defining, documenting, and applying data standards tailored to synthetic chemistry (reagents, solvents, operating conditions, performance, yields, etc.) * Implementing quality and completeness indicators to monitor data robustness and evolution * Contributing to data modeling (schemas, ontologies, reference frameworks) to facilitate future use Phase 2 - Scientific Exploitation and Knowledge Generation Once the data is structured, the VIE will actively contribute to its analysis to extract actionable insights for chemists: * Performing exploratory analyses to identify: * Optimal reaction conditions for given transformations * Historical statistics (success rates, yields, reproducibility, variability) * Detecting recurring patterns, trends, and key success or failure factors in chemical reactions * Producing analyses, visualizations, reports, and summaries directly usable by chemistry teams * Contributing to the development of data-driven decision-support tools based on historical datasets Phase 3 - Integration into Modern Systems and Advanced Perspectives At a later stage, the mission will aim to ensure the sustainability and operational use of the data: * Making datasets compatible with modern systems (ELN, LIMS, internal chemical databases) * Preparing data for advanced research based on chemical structures (annotation, reaction mapping, feature extraction) If data maturity allows, contributing to: * + Exploration or development of predictive models (Machine Learning / AI) + Supporting the prediction of reaction conditions, performance, or probability of success ## Related Videos - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript) - [Vectorize all the things! 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