Research Fellow (National Perinatal Epidemiology and Statistics Unit)

UNSW

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profile Job Location:

Sydney - Canada

profile Monthly Salary: $ 127 - 150
Posted on: 04-11-2025
Vacancies: 1 Vacancy

Job Summary

Research Fellow (National Perinatal Epidemiology and Statistics Unit)

  • Employment Type: Full - time (35 hours a week)
  • Duration: 2 Year Fixed Term
  • Remuneration: $127k - $150k base (17% super and leave loading)
  • Work rights: Visa sponsorship is not available for this position. Candidates must hold full rights to work in Australia to be considered for this position.
  • Location: Kensington NSW

The National Perinatal Epidemiology and Statistics Unit (NPESU)

The NPESU is a unit of the Centre for Big Data Research in Health (CBDRH) strategically partnered with the School of Clinical Medicine (Womens Health) at the University of New South Wales Sydney (UNSW). This positioning places the NPESU at the ideal intersection between clinical and public health research thereby leveraging cutting-edge expertise in managing and analysing large-scale complex health data.

The Opportunity

The Research Fellow will be expected to carry out independent and/or team-based epidemiological and statistical research using large health datasets. The Research Fellow will provide support across projects within the National Perinatal Epidemiology and Statistics Unit (NPESU) in the Centre for Big Data Research in Health.

Some key skills and experience required:

  • A PhD in biostatistics epidemiology or applied statistics or a postgraduate qualification in one of these fields plus relevant research experience.
  • Demonstrated track record in epidemiological research with outcomes of high quality and high impact with clear evidence of the desire and ability to continually achieve research excellence as well as the capacity for research leadership.
  • Strong understanding of theory and methods relating to the design of epidemiological studies and the statistical analysis of population and linked health data.
  • Demonstrated experience in the management and analysis of large complex linked data.
  • Experience in prediction modelling and/or causal inference methods will be highly advantageous.
  • Demonstrated ability to maintain the strictest confidentiality when dealing with sensitive data and an understanding of ethical principles relating to privacy and confidentiality.
  • Highly developed data analysis skills and experience in the use of several statistical packages.

UNSW Benefits and Culture:

UNSW offer a competitive salary and access to a plethora of UNSW-perks including:

  • Flexible working
  • Additional 3 days of leave over the Christmas Period
  • Access to lifelong learning and career development
  • Progressive HR practices

More information on the great staff benefits and culture can be found here.

How to apply:

Please click on Apply now to apply online. Applications should not be sent to the contact listed below. Please provide a resume and a cover letter addressing the main skills and experience listed in the position description. A copy of the Position Description can be found on .

Contact:

Dr Wentao Li email:

Applications close:Monday 24th November before 11.30pm Sydney time.

UNSW is committed to equity diversity and inclusion. Applications from women people of culturally and linguistically diverse backgrounds those living with disabilities members of the LGBTIQ community; and people of Aboriginal and Torres Strait Islander descent are encouraged. UNSW provides workplace adjustments for people with disability and access to flexible work options for eligible staff. The University reserves the right not to proceed with any appointment.

Research Fellow (National Perinatal Epidemiology and Statistics Unit)Employment Type: Full - time (35 hours a week)Duration: 2 Year Fixed TermRemuneration: $127k - $150k base (17% super and leave loading)Work rights: Visa sponsorship is not available for this position. Candidates must hold full righ...
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Key Skills

  • Bioinformatics
  • Genetics
  • R
  • Biochemistry
  • Cell Biology
  • Research Experience
  • Statistical Software
  • Cell Culture
  • Molecular Biology
  • Data Analysis Skills
  • Flow Cytometry
  • Microscopy