19 AI Research Scientist jobs in Australia

What We Are Looking For

About the Team

This position will be a key member of the Electronics Solutions team located in Edinburgh, SA which provides engineering services for the design and build of systems to manage large quantities of imagery, and apply deep learning through convolutional neural networks and other machine learning models to augment imagery analysis.

About The Role

Under the supervision of the Technical Lead, undertake Machine Learning design and development activities as part of the larger engineering project team. You will be working with Researchers and Data Engineers at DST, this role includes utilising and adapting open-source machine learning libraries to assist with automation of computer vision tasks for Analysts.

What Qualifications You Should Have

What are we looking for?

Rheinmetall seeks applicants who exemplify our Company’s values of Safety, Partnering, Openness, Respect and Trust (SPORT) . This creates a workplace environment where employees value each other, live up to their promises and communicate openly.

The experience and skillset best suited to this role includes:

• Experience in development of Machine Learning systems;
• Knowledge in Machine Learning and/or AI;
• Good understanding of best practice DevOps;
• Experience with the software development lifecycle (CI/CD process);
• Knowledge in software environments such as C++, Python, JAVA, JavaScript. RestFul interfaces, Docker;
• Imagery Analysis experience;
• Knowledge in Object Orientated design methodologies and SQL;
• Exposure to developing applications using Linux OS and API’s;
• Ability to travel internationally and interstate, when required; and
• A NV1 Australian Government Security Clearance (Australian Citizenship required).
  
  
  

• Long weekends every second week with a 9 day fortnight;
• Individualised Flexible Working Arrangements;
• Access to exclusive employee discounts with over 500 retailers to support cost of living;
• Market leading parental leave and loyalty leave accrual for every year of service;
• We are proud to be an Endorsed Employer for All Women with WORK180.
  
  
  

The Company

Cornerstone Health is a purpose-led healthcare organisation committed to increasing access to quality healthcare for all Australians. Through our network of 15+ multidisciplinary medical centres and our telehealth platform, Our Sage, we deliver comprehensive, patient-centred care across general practice, radiology, pathology, dental, allied health, and urgent care. We are redefining primary healthcare by integrating technology, clinical excellence, and operational efficiency.

Job Summary

We are seeking a passionate and skilled Machine Learning & AI Engineer to join our team. This role is ideal for someone with a strong foundation in ML theory and hands-on experience building production-grade AI systems in complex environments. You will work closely with clinical, operational, and technical teams to identify opportunities for automation and intelligent systems across our healthcare ecosystem.

Key responsibilities

• Deep dive into Cornerstone Health’s systems, workflows, and data to identify high-impact AI use cases.

• Design, develop, and deploy ML/AI models for patient triage and appointment optimisation; predictive analytics for staffing, inventory, and patient demand; NLP for clinical documentation, pathology reports, and telehealth transcripts; intelligent routing and automation of administrative tasks.

• Collaborate with cross-functional teams to ensure AI solutions are clinically relevant, ethical, and compliant.

• Build and optimise scalable AI pipelines using MLOps best practices.

• Monitor model performance and continuously improve accuracy, quality, and efficiency.

• Document development processes and ensure alignment with healthcare regulations and standards.

• Stay up-to-date with the latest in AI/ML, especially in healthcare applications.

About you

• Bachelor’s or Master’s in Computer Science, Machine Learning, Biomedical Engineering, or related field.

• PhD in a relevant domain is a plus.

• Proven experience in developing and deploying ML/AI models in production.

• Experience in healthcare, clinical systems, or medical data is highly desirable.

• Familiarity with telehealth platforms, EMRs, or diagnostic systems is a bonus.

Technical skills

• Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn).

• Experience with NLP, computer vision, and time-series analysis.

• Familiarity with healthcare data formats.

• Experience with cloud platforms (AWS, Azure) and MLOps tools (MLflow, Kubeflow).

Soft Skills:

• Strong analytical and problem-solving skills.

• Excellent communication and collaboration abilities.

• Ability to translate complex technical concepts into practical healthcare solutions.

• Thrives in a fast-paced environment while maintaining attention to detail.

• Passion for improving healthcare through technology.

Preferred Qualifications

• Experience with generative AI or reinforcement learning.

• Contributions to open-source or peer-reviewed publications in medical AI.

• Familiarity with regulatory frameworks for AI in healthcare.

What We Offer

• Competitive salary and benefits package.

• Opportunity to shape the future of healthcare delivery in Australia.

• Work with a purpose-led team in a fast-growing organisation.

• Be first in industry to develop groundbreaking AI solutions that directly impact patient care.

If this sounds like the right role for you, Apply Now.

• Position to be based at La Trobe Melbourne Campus.
• An amount of $40,000 per annum for 3.5 years, fee relief additional, fortnightly stipend.
  
  

• a stipend scholarship for three and a half years, with a value of $40,000 per annum (pro-rata), to support your living costs.
• a fee-relief scholarship for up to four years.
• opportunities to work with La Trobe’s outstanding researchers in state-of-the-art laboratories and have access to our suite of professional development programs.
• a collaborative project, including time spent with the Olivia Newton-John Cancer Research Institute and CSIRO.
• opportunities to travel to conferences in Australia and overseas.
  
  

• be Australian citizens, Australian permanent residents, or New Zealand special category visa holders (strict requirement).
• meet the entrance requirements for the Doctor of Philosophy.
• should they be selected, agree to be enrolled full-time and undertaking their research at the La Trobe University Melbourne (Bundoora) campus.
  
  

• have an outstanding record of prior performance.
• have completed a Masters by Research or other significant body of research, such as an honours research thesis or lead authorship of a peer-reviewed publication, assessed at a La Trobe Masters by research standard of 75 or above.
• have outstanding grounding in one or more relevant disciplines including cancer biology, cancer medicine, physics, chemistry, , engineering, machine learning / data science, coding.
  
  

• current academic transcript including Masters / Honours grades (or note completion date).
• a statement outlining:
• their motivation and suitability for this opportunity;
• their specific skills and experience and how these are relevant to the PhD project;
• how this opportunity fits with their career plans.
• a statement confirming that you are currently an Australian citizen, Australian permanent resident, or New Zealand special category visa holder.
  
  

We are a world class research-intensive university. We deliver teaching and learning of the highest quality. We play a leading role in economic, social and cultural development of the North East of England. Attracting and retaining high-calibre people is fundamental to our continued success.

Salary

Research Assistant - £28,756 to £0,497 per annum

Research Associate 1,406 to 3,309 with progression to 0,927 per annum

Closing Date : 15th February 2022

The Role

This exciting Research Assistant/Associate position is for a Machine Learning expert who will join a multi-national European project. The candidate will become a member of the ICOS Research Group ( and work under the direction of Prof. N. Krasnogor and Dr E. Torelli.

During the project, you will have the opportunity to investigate, develop and apply machine learning techniques, in collaboration with consortium partners, to datasets derived from real-world experimental data.

You will have the opportunity to contribute towards data sets definition, federation and collection; data capture from instruments and experiments; data wrangling, etc. You will create deep learning tools for predicting experimental outcomes and process optimisation. You will have the opportunity to work on an integrated loop in which every round of machine learning prediction can be used to improve the experimental activities carried out by the consortium and hence gather more and better data for the next round of iterations.

You will work towards the milestones set out for Newcastle within this multi-national project. Furthermore, the researcher will keep excellent records of all computational experiments, procedures, protocols, workflows and outcomes, enabling reuse, interpretation by team members and delivery of project milestones. You will be responsible for reporting to the consortium and publishing the work (either as papers or software or both).

We are seeking a dedicated individual with demonstratable communication skills, a consummate team player with the ability to produce actionable machine learning workflows of a high quality at an experienced level. We are looking for a committed individual with exceptional talent. As part of our drive to build a stellar team, the final selection of short-listed candidates will involve (a) a pre-interview practical exercise, (b) a remote video interview, (c) a post-interview exercise and (d) a collection of at least 2 satisfactory reference letters. Shortlisted candidates who complete this process (whether successful or not will have an inconvenience expense paid). Candidates who are not prepared to fulfil steps (a, b, c & d) should not apply. Candidates close to completing their PhDs can apply.

This position is available on a full time, fixed term basis, to start immediately and is tenable for 24 months from the start date, or until the official project end date, whichever is soonest.

Relocation to the United Kingdom is not required and remote applicants are welcome to apply.

For any informal enquiries please contact Prof. Natalio Krasnogor, Professor of Computing Science and Synthetic Biology via email:

Key Accountabilities

Design, implement, test and debug the entire integrated machine learning workflow for the consortium Establish the data sets strategy for the consortium including data sets definitions, data capture, federation and collection architecture, data wrangling, etc. Utilise state-of-the-art machine learning toolkits to bootstrap the ML infrastructure and -if appropriate- create new toolkits for unmet challenges Development of repeatable computation protocols for the above demonstrating the successful operation of the consortium’s ML workflow, including regular software releases via a version control system Contribution to writing scientific papers and project reports Oral presentations at scientific meetings, workshops, conferences as well as business & consortium meetings The Person (Essential)

Knowledge, Skills And Experience

Demonstrable experience establishing machine learning infrastructures from data acquisition to actionable ML predictions Demonstrable experience with deep learning and other machine learning techniques Demonstrable experience with state-of-the-art ML software packages Demonstrable experience with cloud computing infrastructure for machine learning applications Demonstrable software engineering experience including version control Desirable

Demonstrable experience publishing in peer-reviewed outlets Demonstrable experience in laboratory automation Demonstrable experience applying ML to bioinformatics, chemoinformatics, nanotechnology or biotechnology Demonstrable experience working with scientists and engineers across different discipline Presentation of work at technical as well as more general stakeholders meetings Attributes and Behaviour

Excellent communication skills both oral and written (e.g software documentation, technical reports, papers, presentations, pitches, etc) Capacity for original thought and independent action Enthusiastic, hardworking and goal-setter Ability to interact with people from different disciplines and, while working as part of a team, drive machine learning infrastructure forward Punctual and generally dependable Qualifications

PhD awarded (essential) in computing science, engineering, mathematics or a very closely related discipline (Associate Level) Candidates must be able to spend time away from Newcastle visiting collaborators' labs and attending business meetings outside Newcastle, including international conferences and industrial partners The School/Institute holds a bronze Athena SWAN award in addition to the University’s silver award in recognition of our good employment practices for the advancement of gender equality. The University also holds the HR Excellence in Research award for our work to support the career development of our researchers, and is a member of the Euraxess initiative supporting researchers in Europe.

Newcastle University is committed to being a fully inclusive Global University which actively recruits, supports and retains staff from all sectors of society. We value diversity as well as celebrate, support and thrive on the contributions of all our employees and the communities they represent. We are proud to be an equal opportunities employer and encourage applications from everybody, regardless of race, sex, ethnicity, religion, nationality, sexual orientation, age, disability, gender identity, marital status/civil partnership, pregnancy and maternity, as well as being open to flexible working practices.

Requisition ID: 6341