Research Associate in Deep Learning for Cbrn Spread - Canberra, Australia - University of New South Wales

University of New South Wales
University of New South Wales
Verified Company
Canberra, Australia

2 weeks ago

Olivia Brown

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Olivia Brown

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Description

Job no: 524022


Work type:
full time


Location:
Canberra, ACT


Categories:
Post Doctoral Research Associate


Research Associate Deep Learning for CBRN Spread Prediction, UNSW Canberra

Employment type:
Full time, 35hrs


Duration:
Fixed term for a period of up to 12 months

Remuneration:
Level A from $106,337 plus 17% Superannuation


Location:
Canberra, Australian Capital Territory


About UNSW Canberra
University of New South Wales (UNSW) in Canberra has multiple locations in the Nation's Capital.
UNSW Canberra distinguishes itself from other institutions by its commitment to being thoughtful, practical, and purposeful in all endeavors.

This combined approach is integral to the university's impact and contributes to its recognition as one of the top 20 universities globally, as well as a proud member of Australia's esteemed Group of Eight.

Choosing a career at UNSW means embracing an environment where thriving, facing challenges, and engaging in meaningful work are not just encouraged but integral to the university experience.

If you seek a career where you can excel and contribute meaningfully, you've found the right place.

At UNSW, we pride ourselves on being a workplace where the best people come to do their best work.


Why Your Role Matters:


The School of Engineering and Technology (SET) offers a flexible, friendly working environment that is well-resourced and delivers research-informed education as part of its accredited, globally recognised engineering and computing degrees to its undergraduate students.

The School offers programs in electrical, mechanical, aeronautical, and civil engineering as well as in aviation to graduates and professionals who will be Australia's future technology decision makers.


Responsibilities:


Reporting to the Lead Investigator of the grant, the Research Associate position will involve research activity aimed at developing deep learning-based models for predicting the spread of CBRN threats and tasking teams of uncrewed aerial and ground vehicles to collect necessary data to improve predictions.


Who You Are:


  • A PhD in deep learning, computer vision, or a related discipline.
  • A demonstrated ability to conduct innovative and independent research.
  • A record of papers in high quality journals and/or conferences of high ranking in the field.
  • Experience in programming in Python.
  • Ability to conduct tutorials in use of deep learning models and libraries in a University environment and willingness to undertake teaching duties as required.
  • Excellent interpersonal, oral and written communication skills appropriate for interacting effectively team members, collaborators and colleagues across the Faculty.
  • Experience with real and simulated robotics, and sensor data will be highly regarded.
  • Demonstrated ability to work as a member of a multidisciplinary team showing initiative and taking direction as appropriate to the situation.
  • Demonstrated ability to complete tasks within agreed time frames, with suitable supervision.
  • Knowledge of health and safety responsibilities and the ability and capacity to implement required UNSW health and safety policies and procedures.

Benefits and Culture:


UNSW is committed to helping staff balance work-life responsibilities, by providing access to high-quality services, facilities, and flexible work and leave arrangements.


  • Generous superannuation contributions
  • Employee discounts
  • A commitment to lifelong learning
  • UNSWwide strategy to focus on Healthy Body, Heathy Mind, Healthy Places and Healthy Culture.

Eligibility:

The University reserves the right not to proceed with any appointment.


How to apply:

- your CV
- a 2-page pitch addressing the skills and experience outlined in the Position Description.

For further information about UNSW Canberra, please visit: UNSW Canberra
For further information on living in Canberra, please visit: Living in Canberra


Find out more about the lifestyle and benefits when working with UNSW**Position Description


Advertised: 17 Apr 2024 AUS Eastern Standard Time

Applications close: 15 May 2024 AUS Eastern Standard Time
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