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Professional experiences

August 2024 – present: Cheminformatician

  • Support NICEATM
  • Develop carcinogenicity and mutagenicity models using modern AI, including multi-task deep learning
  • Support generative chemistry AI: oracle selection, output analysis, fine-tuning, and benchmarking datasets; Python library development
  • Support software such as OrbiTox and NICE
  • Develop agentic tools with LLM orchestration
  • Project and individual management

July 2022 – August 2024: Principal Cheminformatician

  • Support NICEATM — PFAS group and scientific lead of the Integrated Chemical Environment (ICE)
  • Class-based read-across on flame retardants
  • Developer and scientific advisor for BioBricks.ai
  • Analysis of high-throughput screening data from the ToxCast/Tox21 US program
  • KNIME workflows for regulatory purposes, PBTK modeling, and data formatting
  • Management of the cheminformatics team

June 2021 – July 2022: Bioinformatics lead

  • QSAR models using deep learning for chemicals disrupting steroidogenesis
  • Mixture risk assessment models for combined chemical exposures
  • Enhance the PFAS-Exchange platform using Ruby
  • Bioinformatics support: non-targeted analysis, population modeling, differential gene expression

January 2020 – June 2021: Independent consultant

  • Built a consulting company, including accounting and administration
  • QSAR models for carcinogenicity
  • Chemical space analysis using ChemMaps.com for environmental chemicals
  • Support development of a population-specific anti-diabetic drug

January 2018 – January 2020: Post-doctoral fellow

January 2017 – January 2018: Post-doctoral researcher

  • Molecular dynamics–based QSAR models on BCR-ABL kinases
  • Antibiotics specific for bacterial strains
  • Molecular dynamics simulations on a GPU server
  • Augmented reality application for chemists

September 2012 – May 2016: Joint Ph.D. student

  • Druggability model PockDrug based on 3D protein pockets
  • Salt-bridge molecular environments for docking and 3D modeling
  • Pipelines to retrieve 3D phosphate structural isosteres

2016 (6 months): Post-doctoral researcher

  • Docking scoring optimization, protein–ligand interaction profiling

2012 (7 months): Internship

  • Statistical analysis, machine learning, discriminant analysis, tree-based methods, visualization, clustering, protein pocket characterization

2011 (5 months): Internship

  • Data mining, statistical analysis on structural patterns, molecular interactions

2010–2011 (3 months): Internship

  • Sequence alignments, gene translocation visualization