Artificial intelligence for macromolecular analysis and pharmaceutical ligands design

What we are looking for : We are looking for PhDs in engineering, physics, mathematics, computing science or any related scientific domain with a strong will to apply the AI methods to Structural Biology and Drug Screening. Knowledge of Python and Deep learning libraries are a must. Previous knowledge of Bioinformatics or Biology is highly appreciated, although not compulsory. The Postdoc must propose a research proposal aligned to the presented challenge.

The context : Structural biology is key to understanding biological macromolecules like proteins and nucleic acids, crucial for biological functions and diseases. Cryo-electron microscopy (cryoEM) revolutionizes this field by visualizing macromolecules at near-atomic resolution, facilitating their study in native states. Simultaneously, computational prediction of ligand binding is vital for drug discovery, helping identify therapeutic candidates by how they interact with biomolecules. The synergy of AI tools for cryoEM and ligand prediction accelerates understanding biological systems and developing new treatments.


The problem to address : The journey from pixelated snapshots to precise atomic models is fraught with computational hurdles, requiring a blend of innovative AI techniques and a deep understanding of molecular landscapes. Parallel to this endeavor is the quest to discover ligands that snugly fit into these newly revealed structures, a critical step in the design of new drugs. This challenge involves sifting through vast chemical libraries to find those rare molecules that can bind with high affinity to target sites on the macromolecule.



  • Elucidating the complex structures of biological macromolecules from CryoEM images.
  • Discover ligands that fit into the structures revealed for new drug design.


Expected Outcomes: Robust algorithms and workflows to tackle both problems.

New position open: Software Developer in the Biocomputing Unit (BCU), Instruct Image Processing Center (I2PC), Madrid

Description: We are looking for a candidate with a BSc/MSc in Computer Science, Mathematics, Engineering, Physics or equivalent with software development skills. The candidate will be involved in European and National projects related to cloud and open data technologies, being part of a team in charge of developing data management software for Instruct facilities.

Thus, the candidate will participate in projects that will shape and influence strategies for making research data generated across the Instruct-ERIC infrastructure FAIR (Findable, Accessible, Interoperable, Reusable). This data transformation will involve considerations of the storage, metadata description and deposition of large datasets for use and reuse including artificial intelligence. These data will come primarily from structural biology but can include data from other diverse research domains.

Background: INSTRUCT ERIC is the European Strategic Initiative in the area of Integrative Structural Biology. It is organized as a distributed infrastructure with “Instruct Centers” and the BCU hosts the “INSTRUCT Image Processing Center (I2PC)”.

 BCU is well known in the area of 3D-EM, with over 200 publications in the area of Electron Microscopy and large contributions to open source scientific software, like Scipion, Xmipp and 3DBionotes.

For further information go to INSTRUCT Image Processing Center or  Biocomp web sites.

Location: Madrid 

Required Skills:

  • BSc / MSc in Computer Science, Mathematics, Engineering, Physics or equivalent
  • Programming experience with Python
  • Experience in Linux
  • Medium level of proficiency in written and spoken English

The following skills are considered a “plus”, but are not essential:

  • Experience of the full lifecycle of software architecture, design, and implementation
  • Experience developing web and desktop Python apps
  • Knowledge and some degree of experience using relational and/or noSQL databases.
  • Experience in assisting open source software development teams (GitHub, documentation, user support, collaboration tools…).
  • Interest or experience in scientific data management
  • Interest or experience in biological sciences or bioinformatics
  • Experience in Virtualization: Docker

nterested candidates should send their CV’s and letter of interest to