Senior Research Fellow (Applying digital tools/data science to clinical interventions in mood disorders)
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Job no: 530359
Work type: Full Time
Location: Sydney, NSW
Categories: Senior Research Associate
Senior Research Fellow (Applying digital tools/data science to clinical interventions in mood disorders)
- Employment Type: Part or Full - time (35 hours a week)
- Duration: 1 Year Fixed Term (possible extension funding dependant)
- Remuneration: From $123, 620 (+17% super and leave loading)
- Location: Randwick, Sydney
Why this role matters:
The Senior Research Fellow/Post Doctoral Fellow(s) will contribute to the development of a mood disorders research team at UNSW, aligned with the Black Dog Institute. The team will focus on early intervention in mood disorders (particularly bipolar disorder), as well as phenotyping and a better understanding of the subgroups within the broad group of conditions referred to as Mood disorders.
Proposed projects include a) a clinical trial and further optimisation of a multi-component model of care including digital interventions, b) evaluating the use of digital data and visualisations in clinical practice and c) the use of existing data in understanding the course and evolution of mood disorders and d) the development of new digital tools and data systems. The Senior Research Fellow is expected to carry out independent and/or team research within the field in which they are appointed and to carry out activities to develop their research expertise relevant to mental health and interventions for mood disorders. There is a strong focus on developing and testing new ideas, implementing projects and successfully disseminating new knowledge, evidenced by recent employment or education history.
For full details please review the position description.
Who you are:
- A PhD in a related discipline, and/or relevant work experience.
- Proven commitment to proactively keeping up to date with discipline knowledge and developments.
- Demonstrated track record in 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.
- Conceptualisation and completion of data analyses with skills related to epidemiology, biostatistics and modelling including machine learning methods
- A sound understanding of clinical trials in mental health, including developing, evaluating or translating novel interventions.
- A track record of significant involvement with the profession and/or industry.
- High level communication skills and ability to network effectively and interact with a diverse range of students and staff.
UNSW Benefits and Culture:
UNSW offer a competitive salary and access to a plethora of UNSW-perks including:
- 17% Superannuation and leave loading
- 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.
If you can provide a resume and a separate document addressing the main skills and experience listed in the position description. A copy of the Position Description can be found on JOBS@UNSW.
Contact
Merita O'Connell – Talent Acquisition Consultant
E: merita.oconnell@unsw.edu.au
Applications close: Sunday 16th March before 11.30pm
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.
Position Description
Advertised: AUS Eastern Daylight Time
Applications close: AUS Eastern Daylight Time
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