Research Fellow in AI for Drug Discovery Full-time

Research Fellow In AI For Drug Discovery

Reporting to Professor Barca the Monash Institute of Pharmaceutical Sciences and working in collaboration with QDX Technologies, the focus of this role will be to advance cutting-edge research at the interface of quantum chemistry, artificial intelligence (AI), and drug discovery. The Research Fellow will be part of a world-class team recognised with prestigious honours including the Gordon Bell Prize and the WATOC Dirac Medal.

As the successful candidate, you will contribute to the design and implementation of AI models that integrate quantum mechanical theory with deep learning, enabling rapid and accurate molecular discovery. You will work closely with academic researchers and industry partners to translate research outputs into real-world therapeutic design pipelines.

Key responsibilities include:

• Developing and deploying machine learning models (e.g. graph neural networks, neural force fields, diffusion models) for molecular property prediction and molecular generation.
• Integrating quantum chemistry data (e.g. DFT, MP2) and experimental data into AI-driven pipelines for structure–property learning and reactivity prediction.
• Applying AI models to real-world problems in virtual screening, ligand optimization, and covalent drug design.
• Collaborating with researchers and engineers at the Monash Institute of Pharmaceutical Sciences and QDX Technologies to implement scalable AI–quantum hybrid platforms for drug discovery.
• Publishing peer-reviewed research and contributing to industrial software tools.

To be successful in this role, you will have:

• A PhD in machine learning, computer science, computational chemistry, computational biology, or a closely related discipline.
• Demonstrated experience in the design of machine learning architectures such as GNNs, VAEs, or diffusion models applied to molecular data.
• Strong knowledge of quantum, medicinal chemistry principles and chemical representations; familiarity with physics-informed ML and drug discovery is necessary.
• Proficiency in Python and deep learning frameworks such as PyTorch, JAX, or TensorFlow.
• Experience with C++ and GPU programming.
• A strong growth mindset, attention to scientific rigor, and the ability to thrive in an interdisciplinary, collaborative environment.

At Monash University, work feels different. There's a sense of belonging, from contributing to something groundbreaking – a place where great things happen.