Deploying Cutting-Edge AI Algorithms for Rapid and Novel Biologic Development for Biotherapeutics
Medical, Biological and other Sciences
ABOUT THE INDUSTRY PARTNER
CSL is a global plasma biotechnology company with a diverse drug portfolio, headquartered in Melbourne. The Bioinformatics team within CSL Research works on providing innovative solutions to diverse research problems pertaining to the company’s drug development pipeline.
WHAT’S IN IT FOR YOU?
- Gain real-world, hands-on experience at the interface of computational and experimental biology in a drug development setting.
- Exposure to concepts, methods, and strategies of AI in drug design and development (e.g., de novo protein design, optimisation, and binding prediction).
- Access to leading IT infrastructure, newly commissioned labs and high-throughput equipment for protein engineering and expression.
- Be a part of a multidisciplinary team that has real impact across a wide range of human diseases and therapeutic areas.
RESEARCH TO BE CONDUCTED
The intern will collaborate with the Protein Engineering and Expression and the Data Science teams in establishing AI approaches to target therapeutically-relevant molecules with artificial protein binders. The goal is to integrate emerging computational tools into established protein engineering, production and biophysical characterisation workflows, supporting discovery efforts for next-generation biologics.
The project will begin with a literature review, summarising best practice methods and assessing gaps. The candidate will then select a few best-in-class publicly available methods and evaluate them in a real-life drug development project, assessing results against current standards. The incumbent will employ good software development practices to create modular, well-documented pipelines, and develop data management and collection practices to gather and store data that is required for training AI models/algorithms.
SKILLS WISH LIST
If you’re a postgraduate research student and meet some or all the below we want to hear from you. We strongly encourage women, indigenous and disadvantaged candidates to apply:
We are seeking a talented intern to assess the critical capability of integrating AI into drug development pipelines. The ideal candidate will have experience with AI and ML, with experience in protein design and engineering, particularly with binder design.
If you are a postgraduate research student and meet some or all the below attributes, we want to hear from you.
- PhD candidate in Bioinformatics, Biochemistry or Structural Biology.
- Solid understanding of ML and AI principles and experience with training, tuning and testing models.
- Relevant programming experience (e.g. Python, R, bash etc), managing software enviroments (e.g. github, conda, singularity) and submitting high-performance computing workflows (e.g. slurm, nextflow).
- Experience in high-throughput cloning, recombinant protein expression and purification.
- High level of verbal and written communication skills.
- Ability to operate independently and collaboratively in a fast-paced research environment.
RESEARCH OUTCOMES
An up-to-date literature survey of current methods of protein and complex structure prediction and de novo protein binder design.
- An assessment of the current workflow to identify compute and data requirements to enable AI capabilities.
- A case study that evaluates available AI tools to generate novel binders to clinically relevant targets, providing critical assessments that showcase performance, identify limitations and make recommendations.
ADDITIONAL DETAILS
The intern will receive $3,300 per month of the internship, usually in the form of scholarship payments.
It is expected that the intern will primarily undertake this research project during regular business hours and maintain contact with their academic mentor throughout the internship either through face-to-face or phone meetings as appropriate.
The intern and their academic mentor will have the opportunity to negotiate the project’s scope, milestones and timeline during the project planning stage.
Please note, applications are reviewed regularly and this internship may be filled prior to the advertised closing date if a suitable applicant is identified. Early submissions are encouraged.
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