Machine Learning Researcher

ML/AI Research Scientists - (Scientist, Senior or Principal) (Algorithm Development)
About Nxera Pharma

Nxera Pharma is establishing a new AI enabled discovery initiative to build a high throughput AI and physics driven GPCR discovery engine that augments our world class experimental capabilities and extensive proprietary structural and chemogenomic data assets originating from Heptares Therapeutics. This initiative sits within our newly formed Computational Sciences team alongside Research Informatics, Chem Informatics and Bio Informatics. AI is being deployed across the NxWaveTM platform, trained on the industry’s most extensive proprietary GPCR structure–ligand dataset and paired with our curated chemogenomic library of GPCR focused small molecules.

Our mission is to unlock the vast untapped potential of G-protein-coupled receptors (GPCRs) using computational and experimental innovation to design first-in-class therapeutics across metabolic, neurological, immunological, and rare diseases.

As part of Nxera’s mission to redefine how new medicines are discovered and to fully leverage advances in AI, quantum mechanics and next generation data integration, we are seeking to hire experienced AI Research Scientists at various levels of experience.

We are seeking an AI Senior Scientist with a strong background in algorithm development to expand the AI capabilities that power Nxera’s discovery engine.

You will design, implement, and deploy novel algorithms that accelerate the discovery and optimisation of small molecules and biologics targeting complex GPCR systems.

This role offers the opportunity to apply your algorithmic expertise at the interface of machine learning, chemistry, and structural biology, with direct impact on our internal pipeline and global collaborations.

• Develop new AI/ML architectures and computational methods for:
• De novo molecular generation using diffusion models, VAEs, GANs, and reinforcement learning.
• Protein–ligand interaction prediction/co-folding via 3D graph neural networks (GNNs) and equivariant transformers.
• Conformational landscape modelling and binding free energy prediction using deep physics-informed learning.
• Active learning and Bayesian optimisation for iterative compound selection and design.
• Work closely with computational chemists, biophysicists, and experimentalists to embed algorithms within Nxera’s NxWave™ workflows.
• Translate algorithmic advances into usable models for hit discovery, virtual screening, and lead optimisation.

• Prototype models using PyTorch, Tensor Flow, or JAX.
• Validate AI models against experimental datasets and benchmark performance across internal and public datasets.
• Optimise algorithms for scalability, interpretability, and real-world application.
• Stay at the forefront of AI in molecular sciences — foundation models, diffusion models, self-supervised learning, generative chemistry.
• Contribute to publications, patents, and conferences in AI drug discovery and computational science.

You are a scientist who thrives at the intersection of machine learning and molecular science — rigorous, creative, and eager to solve the toughest problems in modern drug discovery.

• PhD (or equivalent experience) in Computer Science, Computational Chemistry, Applied Mathematics, or related quantitative field.
• 3–7 years of experience in developing and applying AI algorithms in biopharma, biotech, or academic research.
• Strong proficiency in Python and deep learning frameworks (PyTorch, Tensor Flow, or JAX).
• Proven track record in algorithm design for molecular or biological data.
• Experience with graph learning, transformers, or diffusion-based generative models for molecule design.
• Solid understanding of structure-based drug design, chemo informatics, or computational biology.
• Knowledge of GPCR biology or protein–ligand interactions.
• Familiarity with cloud computing and ML-Ops pipelines.
• Contributions to open-source AI or computational chemistry projects.

• Lead the evolution of AI-driven molecular discovery in a company built on scientific…