Kenneth Goossens

Principal Scientist, Computational Drug Discovery

Antwerp Metropolitan Area

About

As a computational chemist, I bring a unique blend of expertise in both traditional physics-based modeling and machine learning to accelerate drug discovery. With extensive experience in an industrial setting, I have contributed to a wide range of projects in multiple therapeutic areas (oncology and inflammation) and at different drug discovery stages, from target validation to lead optimization. Expert in free energy calculations, virtual screening, molecular design, implementing and designing machine-learning based approaches to use within projects or to integrate into traditional workflows, with a solid foundation in python programming. I also take an active role in identifying and implementing new technologies to improve computational workflows, ensuring that the latest advancements in molecular modeling and machine learning translate into tangible project successes. Beyond technical expertise, I am passionate about fostering collaboration to reach maximum efficiency and communication within project teams. I also enjoy mentoring, knowledge-sharing, and raising awareness of computational tools within the broader scientific community. Keywords: Molecular modeling, cheminformatics, AI-driven drug discovery, structure-based drug design (SBDD), ligand-based drug design (LBDD), medicinal chemistry, free energy perturbation (FEP), deep learning, machine learning in chemistry, computational drug design, generative chemistry, virtual screening, QM/MM, molecular dynamics simulations, bioinformatics, data-driven drug discovery, computer-aided drug design (CADD), drug hunter, cloud computing, domino, github

Experience

  • SandboxAQ ()
    • Principal Scientist, Computational Drug Discovery
      Dec 2025 - Present · 8 mos

    • Senior Computational Chemist
      May 2025 - Dec 2025 · 8 mos

  • Galapagos (2 yrs 8 mos)
    • Senior Scientist Computational Chemistry
      Oct 2024 - Apr 2025 · 7 mos

      • Modelling support to oncology and inflammation projects • FEP expert, exploring the latest technologies and providing feedback and coaching to other team members • Working together with data scientists to set up and apply machine learning models in projects • Designing and implementing automated workflows to accelerate research efforts • Interacting with different stakeholders in research projects • Coordination of discovery science activities within multiple project teams

    • Scientist Computational Chemistry
      Sep 2022 - Sep 2024 · 2 yrs 1 mo

  • Postdoctoral Scientist at The Janssen Pharmaceutical Companies of Johnson & Johnson
    Jun 2021 - Sep 2022 · 1 yr 4 mos

    Joint industrial postdoc, collaboration between University of Antwerp and Janssen Pharmaceuticals.

  • PhD Student at Universiteit Antwerpen
    Oct 2017 - Jun 2021 · 3 yrs 9 mos

    Computational investigation of the catalytic mechanism and dynamics of Staphylococcus aureus glycosyltransferase towards development of novel antibiotics.

  • Research Internship at The Janssen Pharmaceutical Companies of Johnson & Johnson
    Feb 2019 - Jul 2020 · 1 yr 6 mos

    Validation of the virtual fragment screening tool "Solvation Energy for Exhaustive Docking (SEED)" and investigation of its potential use in hit and lead discovery.