Medical Statistics jobs in Sydney NSW

Employment Type: 2 year fixed-term contract with possibility to extend

SNAPSHOT OF BENEFITS

• 
  Generous salary packaging to save you income tax on your wages thereby boosting your monthly take home pay (max. $15,900 general expenses + $2,650 meals/accom)

• Ample opportunities for on-going training and development

• Stimulating, diverse and highly international research environment

• Flexible work arrangements e.g. start / finish times

• 18 weeks paid parental leave for both parents including paid superannuation

• A range of additional leave types to meet your personal needs including cultural leave, conference leave, community service and study leave

• Discounted Health Insurance

• Lifestyle discounts with our community partners

WHAT YOU WILL DO

Depending on level of experience and requirements of the role, a Research Assistant is typically expected to:

1. Scientific Excellence

• Experimental Execution: Developing, maintaining and executing bioinformatic pipelines/workflows, particularly in relation to scRNA-seq and spatial transcriptomic data.

• Optimisation: Contribute to the existing codebase in collaboration with other team members, including debugging, refactoring and enhancing legacy code. Adopt, test and benchmark analytical packages for incorporation into analyses and standardised pipelines.

• Data management: Track, archive and actively manage raw and processed data in accordance with established procedures and policies

• Specialist Advice: Provide technical advice to researchers within the group regarding specific research methods, instruments, and analysis tools.

• Data integrity: Ensure all research data is accurate, high-quality, and conforms to good scientific practice, ensuring it is accessible to other researchers as required.

• Scientific Communication: Communicate experimental results to researchers and collaborators through written reports and effective visual formats.

• Scholarly Contribution: Assist In the preparation of research papers and contribute content to grant applications and research proposals.

2. Team Leadership

• Mentorship & Training: Train students, postdocs, and peers on data collection, specialised tools, and laboratory safety protocols.

• Personal Growth: Take responsibility for own professional development by attending workshops and seeking to learn new techniques to support the group’s evolving research needs.

• Team Collaboration: Work effectively as a reliable and approachable member of the research team, fostering a collaborative environment.

3. Resources & Planning

• Lab Coordination: Manage internal communications, such as scheduling team meetings and research presentations.

• Compliance & Outputs: Manage research data and outputs to ensure compliance with open access requirements of funding bodies and publishers.

• Project Delivery: Balance the competing needs and timelines of multiple research projects within the lab and with external collaborators to meet deadlines.

4. Institute Contributions

• Values & Integrity: Demonstrate scientific and professional integrity at all times, acting as a role model for ethical behaviour.

• Active Participation: Contribute to the wider institute community by participating in committees, outreach projects, or donor activities.

5. Health & Safety and Risk Management

• Comply with Garvan’s workplace polices (as amended from time to time) and especially Garvan’s Work Health & Safety (WHS) Policy, including working in accordance with the WHS management system at all times, as safety is Garvan’s number one priority.

• Proactively identify, assess, and report operational, financial, and safety risks associated with the duties of this role. The incumbent is required to adhere to the organisation’s Risk Management Framework, ensure all activities are conducted in accordance with established policies and procedures, and contribute to a culture of continuous improvement by suggesting mitigation strategies for identified hazards or inefficiencies.

ABOUT YOU

The key skills and experience include:

Essential Knowledge:

• BSc or MSc in computer science or a quantitative discipline (Computational Biology, Bioinformatics, Mathematics and Statistics, Physics, Software Engineering, or a related field)

• Experience with version control systems, particularly Git

• Experience using R and/or Python programming language

• Familiarity with the Unix command line and high-performance computing environments and/or cloud computing

Desirable Knowledge:

• Knowledge of the fundamentals of molecular biology: DNA transcription and translation

• Experience in the analysis of large molecular datasets, such as whole genome and transcriptomic sequencing data

• Experience in handling, processing, and interpreting large-scale biological datasets derived from scRNA-seq and spatial technologies (such as Visium or Xenium)

• Experience in machine learning, deep learning, and foundational models would be preferred but not essential

• Experience working in a multidisciplinary team

• Appreciation of ethical dimensions of clinical research

Personal Qualities:

• Excellent communication skills for written reports and oral presentations

• Excellent organisational and time management skills

• Strong desire to work co-operatively with other team members

• Commitment to data organisation and implementation of quality controls

• An interest in understanding how cancers evolve and progress

ABOUT GARVAN

Garvan Institute of Medical Research is an independent Medical Research Institute (MRI) in Sydney, delivering scientific and clinical impact on a global basis and in partnership with organisations that share our vision. We are proud to be one of Australia’s largest and most highly regarded MRI’s.

Our vision is global leadership in discoveries to impact and our enduring purpose is to impact human health, by harnessing information encoded in our genome.

We seek to see our world-class discovery research achieve life-changing impacts, not only for individual patients with rare diseases, but for the many thousands affected by complex, common disease.