We're Hiring Innovators

We are looking for a Junior R&D Researcher to join our R&D team. The team develops and benchmarks the computational technologies behind our discovery platforms, including protein-peptide complex modeling, binding affinity prediction, and ADMET and permeability prediction. You will contribute to these projects under the guidance of senior scientists.

• Develop computational pipelines, methods, and models for R&D technologies under the supervision of a senior scientist.

• Review published methods and open-source tools for each task and assess their fit for the use case.

• Adapt existing technologies to our needs, including changes to their source code.

• Collect and curate datasets from public databases and the scientific literature, and build benchmarks to evaluate methods against baselines.

• Document methods, benchmark results, and user guides for the drug discovery and software teams.

• Present progress and results at regular R&D reviews.

• Higher education in biology, biochemistry, chemistry, biophysics, bioinformatics, or a related field.
  
  • Candidates who have not yet completed their degree are also considered if they meet most of the other requirements.

• Strong background in biology and chemistry:
  
  • Protein structure across all levels of organization, conformational flexibility, and structure-function relationships.
  • Non-covalent interactions (hydrogen bonds, electrostatic, hydrophobic, π-stacking), covalent binding, and binding thermodynamics.
  • Stereochemistry, protonation and tautomeric states, and physicochemical properties of small molecules and peptides.

• Programming experience in Python: functions, classes, and data structures; conventional libraries for Data Analysis and visualization (Pandas, Numpy, etc.); Conda environments.

• Basic knowledge of machine learning: training, validation, and test splits; standard metrics (ROC-AUC, PR-AUC, RMSE).

• Experience with RDKit, Biotite, or Open Babel, and with structure file formats (PDB, mmCIF, SDF, MOL2).

• Basic experience with Linux and Git.

• Working proficiency in written and spoken English: the ability to write about scientific topics, and to discuss them and make decisions with an international team.

• Hands-on experience with molecular docking (for example AutoDock Vina, Glide, GOLD, or HADDOCK) and an understanding of docking types (rigid and flexible, physics-based and ML-based).

• Experience with other structure-based design methods: structure prediction (AlphaFold, Boltz), binding-site detection, pharmacophore analysis.

• Experience with molecular dynamics simulations (for example GROMACS, AMBER, or OpenMM).

• Experience with molecular visualization tools (PyMOL, ChimeraX, or VMD).

• Experience with PyTorch on GPU, or knowledge of graph neural networks or Transformers.

• A thesis, research internship, hackathon, or personal project in computational drug discovery. A pipeline that you assembled yourself is a strong plus.

• Experience running computations on remote machines, cloud platforms, or HPC.

• Work on real R&D projects in drug discovery, with mentoring from senior scientists.

• Your technologies will be used in drug discovery programs of major pharmaceutical companies.

• Daily work at the intersection of structural biology, chemistry, and machine learning.

• Remote work with flexible collaboration.

• Professional growth in a fast-moving scientific field.

• Curiosity and initiative in research tasks.

• Reliability: you respect deadlines, meetings, and other people's time.

• Honesty, transparency, and openness to feedback.

• Clear communication: you ask immediately when something is unclear.

We’re looking for a Senior-level computational chemist to join our discovery team and contribute to live hit-to-lead and lead optimization projects. You’ll play a key role in connecting in silico modeling with medicinal chemistry to design better compounds across a wide range of targets. Beyond hands-on modeling, you’ll be expected to take an active role in shaping project strategies, planning modeling efforts, and influencing prioritization decisions based on data.

• Support compound design using molecular modeling tools (e.g., docking, molecular dynamics, FEP, pharmacophore design).

• Interpret SAR data, suggest new analogs, and prioritize compound ideas.
  

• Collaborate with medicinal chemistry teams.
  

• Contribute to planning project workflows and setting modeling priorities.
  

• Drive hypothesis generation and test cycles based on evolving data.
  

• Apply both structure- and ligand-based design strategies.
  

• Contribute to data-driven iteration and project decision-making.

• Ph.D. in Computational Chemistry, Medicinal Chemistry, or a related field with 2–5 years of experience in drug discovery
  – OR –
  Master’s degree with 5+ years of hands-on industry experience in computational drug discovery or related roles
  

• Proven track record of contributing to hit identification, hit-to-lead, or lead optimization programs
  

• Proficiency in molecular modeling platforms
  

• Strong understanding of medicinal chemistry and SAR interpretation
  

• Comfortable working in fast-moving, cross-functional project teams

• Drive real drug discovery with visible impact on pipeline progress
  

• Join a science-first team blending AI and chemistry for next-gen therapeutics
  

• Enjoy flexible working with support for remote collaboration

Is actively contributed to real drug discovery projects and can confidently apply modeling techniques to impact design decisions. Is comfortable balancing scientific depth with practical prioritization and can independently plan and drive modeling strategies within multi-disciplinary projects.

We’re looking for a Business Development Representative (BDR) to help expand our collaborations with pharma and biotech organisations. This position is ideal for individuals with a scientific background who want to grow into the business and partnering side of drug discovery while staying close to the science.

You’ll work across scientific, commercial, and operational teams, gaining hands-on exposure to how AI-powered drug discovery partnerships are built.

• Build and maintain relationships with prospective partners across pharma and biotech.
  

• Adapt and improve outreach materials for emails, calls, and meetings.
  

• Review and prepare pipeline opportunities for client discussions.
  

• Support the translation of scientific capabilities into clear value propositions.
  

• Assist with outreach, agenda preparation, meeting coordination, and follow-ups.
  

• Capture scientific and strategic insights from conversations and events.

• Organize client feedback and inputs to ensure smooth collaboration across scientific and business teams.

• Bachelor’s degree in Biology, Molecular Biology, Computational Biology, or a related field.
  

• Understanding of fundamental drug discovery concepts (e.g., target identification, screening, lead optimization).
  

• Strong communication and interpersonal skills.
  

• English proficiency B2+.
  

• Curiosity, adaptability, and willingness to learn both scientific and business aspects of the role.

• Experience in sales outreach, BD, or scientific communication.
  

• Interest in AI applications in biology or chemistry.