Full-time, 12-month fixed-term role, with the possibility of extension Dynamic opportunity for a Data Science expert to apply their skills to mental health research Base Salary $108,557 - $118,267 + 17% superannuation About the opportunityThe University of Sydney's Brain and Mind Centre is a centre for discovery, innovation and integrative research strategies, clinical product development and actions that translate research into improved treatment and disease prevention strategies. The centre is made up of 27 research units, staffed by around 200 researchers and 100 students.
The Youth Mental Health and Technology team puts young people at the centre of their own care. We partner with health services to develop innovative treatments for those aged 12-25 with emerging mental health disorders. The integration of cutting-edge research with safe and effective clinical care enables us to quickly and effectively translate our research findings into clinical services, facilitating continuous improvements to mental health services for the benefit of young people in Australia.
We are looking for a Data Scientist to contribute across our sub-teams in youth mental health. As the successful candidate, you will be applying modern data science methods to build explainable machine learning models, performing data wrangling and engineering for informed decision-making tools, and supporting other data science initiatives in the Youth Mental Health and Technology team whilst reporting to the Senior Data Scientist.
Your key responsibilities will be to:Support the objectives of the research program by conducting data wrangling from disparate data sources to form the basis of system dynamics models.Contribute to the development of novel methodologies to model illness trajectories in youth mental health and facilitate their application and use in health services utilising digital technologies.Work within a team of senior academics, data scientists, mathematical modellers, data engineers and clinicians to deliver high-quality research outputs and collaborate with the team to develop ideas for grant applications.About youBachelors in a relevant field (Masters desirable)
2 years+ experience in mathematics, statistics and/or data science roles (or related relevant fields)
Fluency in the R programming language and proficiency in R data science and wrangling packages (tidyverse)
Experience in wrangling data from disparate sources into formats for statistical analysis
Knowledge in probabilistic machine learning, including Bayesian modelling and inference and longitudinal modelling, preferably applied to the field of mental health
Experience dealing with real-world data sets, including heterogeneous structured data with missing or unreliable fields
Possess excellent communication skills, organisational and interpersonal skills
Ability to work effectively, collaboratively as part of a multidisciplinary team
Ability to work independently and complete tasks on time with minimal supervision
Passion for the application of data science to youth mental health.
Sponsorship / work rights for AustraliaPlease note: Visa sponsorship is not available for this position. This role requires valid work rights for Australia.
Your employment is conditional upon the completion of all role required pre-employment or background checks in terms satisfactory to the University. Similarly, your ongoing employment is conditional upon the satisfactory maintenance of all relevant clearances and background check requirements. If you do not meet these conditions, the University may take any necessary step, including the termination of your employment.
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About UsThe University values courage and creativity; openness and engagement; inclusion and diversity; and respect and integrity.
The University of Sydney is committed to diversity and social inclusion. Applications from people of culturally and linguistically diverse backgrounds; equity target groups including women, people with disabilities, people who identify as LGBTIQ; and people of Aboriginal and Torres Strait Islander descent, are encouraged.
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