The Vall d´Hebron Institute of Oncology (VHIO) Seeks a Machine Learning Scientist – AI for Small-Molecule Drug Discovery

Reference: 2025-019-01

Application deadline: 03/07/2026

Number of vacancies: 1

Job description:

The AI-Driven Drug Discovery Group at the Vall d’Hebron Institute of Oncology (VHIO) in Barcelona, led by Dr. Albert Antolin, is seeking an outstanding Machine Learning Scientist to contribute to the development of next-generation ML methods for small-molecule drug discovery. The successful candidate will be funded by and play a leading role in the five-year, European Innovative Health Initiative (IHI) project LIGAND-AI (https://ligand-ai.org/), a large-scale public-private consortium within the Open Science Target 2035 initiative involving leading academic institutions and pharmaceutical and technology partners including Pfizer, IBM and the Structural Genomics Consortium. LIGAND-AI aims to generate ultra-large-scale ligand binding data to enable the development of next-generation machine learning methods for hit discovery against challenging therapeutic targets (Edwards AE, et al. Nature Reviews Chemistry, 2025).

This is a strategic and highly collaborative position offering a unique opportunity to help shape emerging machine learning approaches for DNA-Encoded Libraries (DEL), ultra-large chemical spaces and AI-driven small-molecule drug discovery. The candidate will have access to unique large-scale datasets generated through the LIGAND-AI consortium and will contribute to the development of innovative DEL-ML methodologies and translational drug discovery applications while interacting closely with international academic and industry collaborators.

https://vhiovidaprogramme.eu/wp-content/uploads/2025/08/GroupDescription_Albert-antolin.pdf

Responsibilities

• Lead the development of machine learning and deep learning methods for early small-molecule drug discovery, particularly for DNA-Encoded Libraries (DEL), hit discovery, prioritization and hit-to-lead optimization.

• Drive the lab’s scientific contributions to the IHI LIGAND-AI consortium and related Target 2035 activities.

• Contribute to the design and lead our participation in DEL-ML benchmarking challenges (such as the 1st Target 2035 DREAM Challenge).

• Apply ML methods in translational drug discovery campaigns in collaboration with experimental scientists.

• Collaborate closely with international academic and industry partners, including pharmaceutical and technology companies.

• Present results at consortium meetings and international scientific conferences.

• Lead the scientific publication of your work and contribute to new grant applications.

• Co-mentor junior researchers and contribute to the establishment of reproducible and scalable ML workflows in the group.

Requirements

Studies Required

• PhD in machine learning, artificial intelligence, cheminformatics, computational chemistry, or a related discipline.

Studies Complementary

• Training in drug discovery, medicinal/computational chemistry.

• Training in deep learning, molecular modelling or large-scale data analysis.

Knowledge Required

• Strong knowledge of machine learning and deep learning methodologies.

• Strong programming skills in Python and experience with modern ML frameworks (e.g. PyTorch, TensorFlow, etc.).

• Good working knowledge of Unix/Linux environments and reproducible computational workflows.

• Excellent command of English, both written and spoken.

Knowledge Complementary

• Knowledge of DNA-Encoded Libraries (DEL) and DEL data analysis.

• Knowledge of hit discovery, virtual screening or other drug discovery workflows.

• Familiarity with chemical foundation models, graph neural networks, transformers,geometric deep learning and/or molecular representation learning.

Experience Required

• Proven track record in machine learning applied to small-molecule drug discovery, chemistry, or related domains, evidenced by peer-reviewed publications and/or impactful software development.

• Experience with high-performance computing environments.

Experience Complementary

• Previous experience in academia-industry collaborative projects or in collaborativemultidisciplinary research environments or large-scale projects.

• Experience mentoring students or junior researchers.

• Experience contributing to open-source computational projects or benchmark initiatives.

• Experience applying AI methods and collaborating with medicinal chemists, chemical biologists, or other experimental scientists in prospective drug discovery projects.

• Experience working with chemical representations, ultra-large chemical spaces, or cheminformatics tools.

• Experience working with experimental datasets characterized by measurement uncertainty or noise (e.g. DEL data).

• Experience developing machine learning methods that generalize across targets, chemical series, or experimental datasets.

Skills

• Ability to work independently and drive ambitious scientific projects.

• Strong analytical and problem-solving skills.

• Excellent communication and presentation skills.

• Ability to collaborate effectively within multidisciplinary international teams.

• Strong organizational and project management skills.

• Proactive, creative and solution-oriented mindset.

Additional information:

We offer:

• 📈The possibility of developing your professional career in a competitive environment.

• 🧠To be part of a center that is constantly developing, pursuing excellence in research and collaborating with leading teams.

• 🫱🏻‍🫲🏾We offer and promote a diverse and inclusive environment, and welcome all people equally, regardless of age, disability, gender, nationality, race, religion or sexual orientation.

• 🪴We care about our environment and understand the importance of sustainability. We have the GreenVhio program, which you can be a part of.

Conditions:

• 🗓️Full-time position, 37.5 hours per week.

• 💶 📝 Salary and contract: The successful candidate will be funded by and play a leading role in the five-year, European Innovative Health Initiative (IHI) project LIGAND-AI (https://ligand-ai.org/).

• 💳Flexible remuneration program (includes restaurant vouchers/cards, transport, medical insurance, and “baby daycare” voucher).

• ⏰Flexible working hours and measures to balance work, family, and personal life, and promote gender equality, as established in the VHIO collective agreement.

• 🗺️24 days of holidays and 6 personal days.

• 🎓Fully subsidized Catalan, Spanish, or English courses.

• 🏃‍➡️Take advantage of doing sports at great prices with Urban Sports Club.

• 🩺You’ll have access to weekly physiotherapy sessions at the office, offered at a reduced price for the team.

Vall d’Hebron Institute Oncology (VHIO) endorses the Requirements and Principles of the European Charter for Researchers, the Code of Conduct for the Recruitment of Researchers promoted by the European Commission and follows Equal Opportunities policies.

On 10th April 2018 VHIO was awarded the “HR Excellence in Research” logo. Our Institute was consequently granted permission to use the HR Excellence in Research Award logo as demonstration of its stimulating and favourable work environment in line with the Charter & Code.