The Opportunity
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.
About You
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.
About Monash University
At Monash, work feels different. There’s a sense of belonging, from contributing to something groundbreaking – a place where great things happen.
We value difference and diversity, and welcome and celebrate everyone's contributions, lived experience and expertise. That’s why we champion an inclusive and respectful workplace culture where everyone is supported to succeed.
Together with our commitment to academic freedom, you will have access to quality research facilities, infrastructure, world-class teaching spaces, and international collaboration opportunities.
Learn more about Monash.
To Apply
For instructions on how to apply, please refer to 'How to apply for Monash Jobs'. Your application must address the Key Selection Criteria.
Diversity is one of our greatest strengths at Monash. We encourage applications from Aboriginal and Torres Strait Islander people, culturally and linguistically diverse people, people with disabilities, neurodivergent people, and people of all genders, sexualities, and age groups.
We are committed to fostering an inclusive and accessible recruitment process at Monash. If you need any reasonable adjustments, please contact us at hr-recruitment@monash.edu in an email titled 'Reasonable Adjustments Request' for a confidential discussion.
Your employment is contingent upon the satisfactory completion of all pre-employment and/or background checks required for the role, as determined by the University.
Enquiries: Professor Giuseppe Barca, Professor of Quantum Medicinal Chemistry Ph: +61 3 9903 9543
Position Description: Research Fellow
Applications Close: Thursday 11 September 2025, 11:55pm AEDT
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