Machine learning Jobs at Australian Universities

Dates

Opening Date: 21-Aug-2024
Closing Date: 23-Sep-2024

Responsibilities

Establish and build a dynamic research program in computer vision or machine learning.
Ensure trans-disciplinary collaboration across the wider academic community.
Enhance industry engagement both nationally and globally.
Manage a startup package to establish local research capabilities.

Requirements

A PhD in the field of computer science or an equivalent qualification.
A research track record of international distinction and sustained excellence in machine learning, computer vision or artificial intelligence.
Demonstrated ability to develop research programs of scope and scale, supported by research funding.
Demonstrated ability to forge meaningful external relationships with non-academic partners and industry.
Demonstrated ability to attract and supervise postgraduate students.

Benefits

Salary packaging
Flexible work arrangements
High-quality professional development programs and activities
On-campus health clinic, gym and other fitness facilities.

Notes

The University reserves the right to close this advertisement before the closing date if a suitable candidate is identified.
Female applicants, people with a disability and/or Aboriginal and Torres Strait Islander people who meet the requirements of this position are strongly encouraged to apply.

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Dates

Opening Date: 21-Aug-2024
Closing Date: 30-Sep-2024

Location

Adelaide, South Australia, 5005 Australia

Salary

$162,460 to $178,700 per annum plus an employer contribution of 17% superannuation applies.

Responsibilities

Establish and build a dynamic research program in computer vision or machine learning.
Ensure trans-disciplinary collaboration across the wider academic community.
Enhance industry engagement both nationally and globally.
Develop research programs of scope and scale, supported by research funding.
Forge meaningful external relationships with a diverse range of non-academic partners and industry.
Attract and supervise postgraduate students.

Requirements

A PhD in the field of computer science or an equivalent qualification.
A research track record of international distinction and sustained excellence in machine learning, computer vision or artificial intelligence.
Demonstrated ability to develop research programs of scope and scale, supported by research funding.
Demonstrated ability to forge meaningful external relationships with a diverse range of non-academic partners and industry.
Demonstrated ability to attract and supervise postgraduate students.

Benefits

Salary packaging
Flexible work arrangements
High-quality professional development programs and activities
On-campus health clinic, gym and other fitness facilities.

Notes

The University reserves the right to close this advertisement before the closing date if a suitable candidate is identified.
For a confidential discussion regarding this position, contact Professor Simon Lucey or Dr Kathy Nicholson.

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Dates

Opening Date: Not Available
Closing Date: 22-Sep-2024

Location

Canberra / ACT, ACT, Australia, 2601

Salary

$112,693 – $120,506 per annum, plus 17% superannuation

Responsibilities

Implement and maintain efficient, scalable AI/ML and data analysis algorithms.
Optimise large-scale parallel I/O operations in HPC systems.
Engage with internal and external stakeholders to understand requirements and coordinate developments.
Stay up to date with the latest developments in HPC and data science related technologies.

Requirements

Experience developing and using Machine Learning frameworks and algorithms
Experience using high-performance computing systems for large-scale data processing and analysis
Self-learner, good listener, accountable and passionate about helping others as well as working in a collaborative team environment
Detail-oriented with an ability to handle multiple issues, tasks and competing priorities concurrently
Remain up to date on latest trends and technologies
Commitment to a safe, inclusive and respectful workplace environment
Linux/Unix experience (desirable)
Expert knowledge of common data formats used in climate and geoscience data (e.g., netCDF, HDF5, zarr) (desirable)
Experience using GPU applications and cloud computing environments for large-scale data processing and analysis (desirable)
Experience with compiled scientific programming languages (e.g., Fortran, C++) (desirable)

Benefits

Flexible working arrangements to encourage a healthy work/life balance, including consideration of part-time roles.
Exceptional workplace culture with a supportive, diverse and inclusive team.
Great work location with world-class staff amenities including gyms, swimming pool, childcare centres, etc.
Excellent remuneration and conditions, including 17% superannuation contributions, annual leave loading and a range of benefits.

Notes

The successful candidate must have rights to live and work in this country and will be required to undergo a background check during the recruitment process. An offer of employment is conditional on satisfactory results.

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Dates

Opening Date: 11-Sep-2024
Closing Date: 07-Oct-2024

Location

Sydney, NSW

Salary

$123,044-$138,637 + 17% super + leave loading

Responsibilities

Assess and deploy computational structural biology software tools and workflows across various compute infrastructure platforms.
Provide direct support and guidance to researchers in applying computational structural biology methods, with a focus on deep learning/machine learning packages.
Collaborate with local and national networks to identify requirements, propose recommendations, and develop approaches to resolve computational challenges.
Lead and support the use of computational tools and best practices through training sessions, practical assistance, and developing documentation.
Report progress with accountability and transparency to the SBF’s Chief Scientist and BioCommons A/Director of Platforms.

Requirements

Relevant tertiary qualification and/or experience specifically in the field of Structural Biology.
Experience in building biomolecular models using techniques such as CryoEM, crystallography, AlphaFold, etc.
Expertise in installing, using, and troubleshooting AI and ML code packages and tools.
Supporting research groups with computational methods, including training and documentation.
Proficiency in git and fluency in Linux/HPC environments.
Excellent written and verbal communication skills, with a high level of attention to detail.
Proven ability to influence senior management and stakeholders to ensure successful outcomes.
High level of organisational, analytical, and problem-solving skills.

Benefits

Supportive and dynamic work environment.
Opportunity to work at the intersection of computational biology, structural biology, and high-performance computing.
Access to specialized instruments and high-performance computing resources.

Notes

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.

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Dates

Opening Date: 02-Sep-2024
Closing Date: 02-Oct-2024

Location

Adelaide, South Australia, 5005 Australia

Salary

(Level A) $78,544 to $105,611 or (Level B) $111,031 to $131,335 per annum plus an employer contribution of 17% superannuation applies.

Responsibilities

Lead AI-driven research in cancer bioinformatics.
Pioneer AI-driven methods to analyze cancer-related biological data.
Uncover novel patterns and mechanisms underlying cancer progression and treatment response.
Collaborate with multidisciplinary experts in cancer research.

Requirements

A PhD in Computational Biology, Computer Science, Artificial Intelligence, or Software Engineering (or equivalent).
A record of quality research in relevant fields, evidenced by publications in leading journals and at conferences.
Experience in machine learning and deep learning.
Proficiency in one or more high-level programming languages such as Python, Java, or R.
Strong commitment to interdisciplinary research and a track record of successful collaborations.

Benefits

Salary packaging.
Flexible work arrangements.
High-quality professional development programs and activities.
On-campus health clinic, gym, and other fitness facilities.

Notes

The University reserves the right to close this advertisement before the closing date if a suitable candidate is identified.
For a confidential discussion regarding this position, contact Fuyi Li, Group Leader, SAiGENCI.

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Dates

31 May 2024 - Advertised
30 Nov 2024 - Applications close

Responsibilities

Apply advanced machine learning and AI concepts to develop systems.
Suggest improvements to machine learning processes and technologies.
Test new AI models and systems for proper performance.
Liaise with other engineers and stakeholders to finalize AI models and systems.
Document AI model development processes and protocols.

Requirements

A degree in a relevant field (e.g., computer science, machine learning, or artificial intelligence) or equivalent knowledge.
Ability to work collaboratively in a team environment and communicate effectively.
Ability to work effectively with minimal supervision, including monitoring workflow and priorities.
Advanced computer literacy and programming ability, with experience in machine learning frameworks and tools.
Proven ability to work effectively with minimal supervision, including monitoring own workflow and priorities.

Benefits

missing

Notes

Please note that you must have working rights in Australia and have an Australian bank account. Overseas applications cannot be considered.

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Dates

28 May 2024 - Job Advertised
24 Jun 2024 - Closing Date

Responsibilities

Engage in individual and collaborative research
Create scholarly impact in the discipline
Conduct research/scholarly activities under limited supervision
Work collaboratively with other researchers
Establish a personal research portfolio
Contribute to the development of applications for competitive funding
Design research projects using advanced statistics and machine learning
Mentor and guide students and colleagues
Maintain focus on communicating research findings
Contribute to collegiate life and UNSW Values in Action

Requirements

PhD in climate/atmospheric science, data science, physics, or relevant discipline
Proven commitment to keeping up to date with discipline knowledge
Track record in research with high-quality outcomes
Experience in machine learning methods in science
Analytical and problem-solving skills
Programming skills in Unix/Linux environment
Experience in weather or climate modeling and handling large datasets
Communication skills and ability to network effectively
Ability to work in a team and collaborate across disciplines
Interpersonal and organizational skills
Understanding and commitment to UNSW's aims and values
Knowledge of health and safety responsibilities

Benefits

Full-time position with fixed term of 4 years
Fully funded position by the Australian Research Council
Contribution to vibrant Centre community
Networking and professional development opportunities

Notes

Position reports to Professor Lisa Alexander
No direct reports
Selection criteria must be addressed in application
Applications close on June 24th, 2024

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Dates

24 Jun 2024 - Closing Date

Responsibilities

Support the day-to-day activities of AIML's Industry Solutions Team
Develop new machine learning algorithms
Produce production code
Analyse data
Deliver machine learning systems for industry partners

Requirements

Proficient in project/product management at a high level
Strong understanding of Agile methodologies and best practices
Experience in identifying and addressing risks and obstacles to project advancement
Exceptional communication skills
Capacity to adapt to changing project demands and priorities
Skilled in fostering a collaborative and inclusive team environment

Benefits

Salary packaging
Flexible work arrangements
Professional development programs
On-campus health clinic and fitness facilities

Notes

Fixed term - Full-time
36 Month Fixed Term Position
HEO8
Faculty of Sciences, Engineering and Technology

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Dates

3rd July - 2023

Responsibilities

Conduct research aligned with the goals of the Centre/Institute to advance knowledge and achieve research objectives.
Develop a strong publication record by publishing research findings in reputable international journals and conferences. Additionally, actively seek competitive funding opportunities for research projects.
Specialise in fine-grain visual classification in agriculture, encompassing fundamental theories, new approaches, algorithms, technical investigations, system implementations, and experiments for research projects.
Collaborate with team members on research projects, contributing to their development and preparation. Foster a collaborative research environment.
Engage in teaching activities as required and provide mentorship and supervision to research higher degree students. Help nurture the next generation of researchers.

Requirements

PhD in computer science, engineering, applied mathematics, or a related field.
Proven track record in conducting research, including publications in esteemed journals and conferences such as IEEE TPAMI, IEEE TIP, PR, CVPR, ICCV, IJCAI, AAAI.

Benefits

Mix of on campus and work from home options available and a supportive work environment.
Salary packaging options and corporate health discounts.
Generous leave entitlements including paid parental leave and leave loading.

Notes

This is a fixed term (2 years), full time position.
The successful candidate will be appointed at either Grade 1 or 2 depending on experience, skills, and qualifications.

Extras

Griffith University values diversity, inclusion, and flexibility. Aboriginal and Torres Strait Islander, and people of all backgrounds are encouraged to apply.

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Dates

Opening Date: 22-Aug-2024
Closing Date: 30-Nov-2024

Responsibilities

Teaching undergraduate and postgraduate courses
Conducting independent research
Delivering excellent teaching
Initiating development of experimental approaches to teaching and learning
Supporting learning progression of students
Managing course administration
Maintaining professional development
Engaging in individual and collaborative research
Creating scholarly impact
Contributing to the development of grant applications
Mentoring and guiding students and colleagues

Requirements

PhD in a related discipline
Relevant work experience
Commitment to keeping up-to-date with discipline knowledge
Experience in teaching and learning design and delivery
Knowledge of industry or work-integrated learning
Track record in research with high-quality outcomes
High-level communication and networking skills
Ability to work in a team
Understanding and commitment to organizational values and policies
Knowledge of health and safety responsibilities

Benefits

Flexible work options
26 weeks of fully paid maternity or primary carers leave
Support services for research, teaching, and career development

Notes

Applications must be submitted online
Encouragement to apply even if experience does not align 100%
Inclusion and diversity commitment
University reserves the right not to proceed with any appointment

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Dates

Opening Date: 02-Sep-2024
Closing Date: 01-Oct-2024

Location

Sydney, NSW

Salary

Not Available

Responsibilities

Investigate quantum advantage with near-term quantum systems.
Explore the implementation of analogue quantum systems on near-term arrays of phosphorus-doped silicon quantum dots.
Explore the implementation of digital quantum algorithms on near-term, atom-based silicon hardware.
Adapt, tailor, and develop analogue quantum systems and quantum algorithms for industry focussed applications.
Work on the theory of analogue quantum systems to better understand the near- and medium-term direction of analogue quantum computing to determine when/how a quantum advantage can be achieved.
Work on the theory of quantum algorithms to better understand the medium- to long-term direction of quantum computing to determine when/how a quantum advantage can be achieved.
Work with a multidisciplinary team of quantum physicists, engineers, technicians, postdoctoral researchers, and PhD students for early-stage quantum system implementations on silicon-based quantum computer devices.
Generate high quality research publication output.
Provide technical assistance and training to the research staff and students working within SQC.
Align with and actively demonstrate the UNSW Values in Action: Our Behaviours and the UNSW Code of Conduct.
Cooperate with all health and safety policies and procedures of the university and take all reasonable care to ensure that your actions or omissions do not impact on the health and safety of yourself or others.

Requirements

A PhD Physics, Computer Science, Mathematics, or relevant field, with work experience in a research or commercial environment.
Demonstrated research capabilities in classical machine learning, quantum machine learning, condensed matter physics, computational physics or related field.
Experience writing high-performance quantum algorithm implementation, preferably in Python, MATLAB, C/C++, or equivalent. GPU programming experience.
Experience with Python quantum computing packages such as OpenQASM (Qiskit), Cirq, Project Q, or equivalent.
Experience in troubleshooting and solving complex unplanned issues.
Well-organised, attention to detail and ability to meet deadlines.
Excellent written and verbal communication skills.
Demonstrated ability to work in a team, collaborate across disciplines and build effective relationships.
An understanding of and commitment to UNSW’s aims, objectives and values in action, together with relevant policies and guidelines.
Knowledge of health and safety responsibilities and commitment to attending relevant health and safety training.

Benefits

Not Available

Notes

This role is a fixed-term position for 3 years.

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Dates

Opening Date: Not Available
Closing Date: 22-Sep-2024

Location

Canberra / ACT, ACT, Australia, 2601

Salary

$112,693 – $134,446 per annum, plus 17% superannuation

Responsibilities

Profile and benchmark parallel code in an HPC environment, identifying bottlenecks and areas where performance can be improved.
Optimise code performance through testing, debugging, and refactoring.
Engage with code owners to gather requirements and coordinate developments.
Explore the use of new technologies, like GPU-based algorithms, machine learning or cloud-based computing, in the context of climate modelling.
Stay up to date with the latest developments in HPC related technologies.

Requirements

Linux/Unix experience
Experience developing scientific software written in Fortran and/or C++
Experience in profiling and optimising code on HPC systems
Self-learner, good listener, accountable and passionate about helping others as well as working in a collaborative team environment
Detail-oriented with an ability to handle multiple issues, tasks and competing priorities concurrently
Remain up to date on latest trends and technologies
Commitment to a safe, inclusive and respectful workplace environment
Desirable: GPU programming (e.g. CUDA, HIP, OpenCL)
Experience developing and/or using Machine Learning frameworks and algorithms.

Benefits

Flexible working arrangements to encourage a healthy work/life balance, including consideration of part-time roles.
Exceptional workplace culture with a supportive, diverse and inclusive team.
Great work location with world-class staff amenities including gyms, swimming pool, childcare centres, etc.
Excellent remuneration and conditions, including 17% superannuation contributions, annual leave loading and a range of benefits.

Notes

An appointment will be made at levels ANU Officer 8 or ANU Senior Manager 1, dependent on the level of experience of the applicant.
The successful applicant must have rights to live and work in this country.
The successful candidate will be required to undergo a background check during the recruitment process. An offer of employment is conditional on satisfactory results.

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Dates

Opening Date: 13-Sep-2024
Closing Date: 29-Sep-2024

Location

Macquarie University, Wallumattagal Campus, North Ryde

Salary

From $106,089 - $113,697 (Level A, Step 6 to Step 8), plus 17% employer superannuation and annual leave loading.

Responsibilities

Lead the development of a low-cost hearing screening device funded by the Cochlear-Macquarie University Joint Fund
Collaborate with leading researchers in hearing science, Cochlear, and mathematicians
Contribute to the development of signal processing and machine learning-based methods to optimize the screening test
Support the research group in developing the next generation of low-cost hearing screening devices
Contribute to other funded projects and help towards implementation of the developed software in hardware devices

Requirements

Hold a PhD in signal processing, machine learning, or a related field such as neuroscience
Experience in signal processing and machine learning
Effective communicator, able to work independently and as part of a team
Advanced programming skills
Strong research skills including planning and conducting experiments
Ability to work collaboratively with a diverse team
Strong organizational skills with a track record of independent and team-based work

Benefits

Opportunities for significant research, networking, and mentoring within a supportive research environment
Access to state-of-the-art research facilities
Opportunities to work with PhD, Masters, and undergraduate students
Full-time, fixed-term position for 3 years

Notes

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Dates

Opening Date: Not Available
Closing Date: 22-Sep-2024

Location

Hawthorn campus, Swinburne University of Technology

Salary

RSCHA/Academic Level A salary (depending on qualifications and skills)

Responsibilities

Oversee the integration of vehicle/occupant monitoring systems in the dedicated research vehicle.
Manage all aspects of data collection, processing, and analysis related to vehicle and occupant monitoring outcomes.

Requirements

Demonstrated experience in administering and delivering successful research projects with internal and external stakeholders.
High degree of proficiency in scripting and/or programming languages (e.g. Python, Bash, R) and version control (e.g. git).
Demonstrated experience in designing and conducting quantitative research with human participants in the field of experimental psychology, human factors, ergonomics or similar.
Experience in generating insight from a large volume of data through methods of statistical analysis and/or machine learning.
An Undergraduate/postgraduate/honours qualification in human factors, psychology, ergonomics, User experience (UX) research or a related field.

Benefits

Flexible working options contained in leave and parenting/carer policies to support work-life balance.

Notes

Appointment to this position is subject to passing a Working with Children Check.
For more information about the role, please email talentacquisition@swin.edu.au.

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Dates

Opening Date: 17-Sep-2024
Closing Date: 15-Oct-2024

Location

Parkville, Victoria, 3010, Australia

Salary

Academic – Level A - $83,468 - $113,262 p.a. | Level B - $119,231 - $141,581 (pro-rata for part time) plus 17% super

Responsibilities

Lead and coordinate advanced computational analyses of fMRI data collected from ongoing and new research projects within the NHMRC Centre of Research Excellence (i.e., using computational methods, including machine learning, network analyses, and graph theory, to extract meaningful insights from neuroimaging data).
Integrate neuroimaging data with clinical, behavioural, and psychophysiological measures to identify biomarkers and predictors of treatment response.
Prepare high-quality manuscripts for publication in peer-reviewed journals and present research findings at national and international conferences.
Contribute to grant writing and funding applications to support ongoing research initiatives.

Requirements

A Ph.D. in neuroscience, psychology, biomedical engineering, computer science, or a related field.
Expertise in human neuroimaging techniques, particularly fMRI.
Demonstrated experience in advanced computational analyses of neuroimaging data, including machine learning, network analyses, and graph theory.
Proficiency in programming languages commonly used in neuroimaging research (e.g., Python, MATLAB, R).

Benefits

Salary packaging
Subsidised health and wellbeing services
Fitness and cultural clubs
Myki discounts
25% discount on graduate courses for staff and their immediate families
Generous leave provisions

Notes

Visa sponsorship is available for this position.
This role requires that the successful candidate must undergo and maintain an up-to-date Working with Children Check.

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Dates

Opening Date: Not Available
Closing Date: 29-Sep-2024

Location

Western Sydney University, Parramatta, Penrith (Kingswood) or Campbelltown Campus

Salary

Academic Level A $106,765 to $128,989 p.a. | Includes 17% Superannuation & Leave Loading

Responsibilities

Develop, design, and deliver innovative and engaging teaching materials for tutorials, demonstrations, and workshops.
Inspire and educate students with a creative approach to teaching.
Engage in meaningful research and share insights through publications and presentations.
Contribute to the academic community and build relationships with colleagues.
Lead research initiatives and strengthen industry partnerships.

Requirements

Engaged as a casual academic for at least 2 teaching sessions within the previous 2 years at an Australian Higher Education institution.
Hold or have submitted all requirements for a PhD or other relevant Level 10 AQF qualification.
Have not previously held an ongoing position with an Australian Higher Education provider in the previous 3 years.
Submit evidence of successful teaching results, such as Student Feedback on Teaching survey outcomes.

Benefits

Opportunity to be part of a sector-leading program to strengthen career pathways for casual academic staff.
Training over the confirmation period to support candidates in retaining stable, ongoing employment.
Engagement in a dynamic academic community.

Notes

These are full-time, ongoing positions commencing from January 2025.
Travel to other campuses of the University may be required.
Interviews are likely to be scheduled between Monday 21st October and Thursday 24th October 2024.

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Dates

Opening Date: 19-Sep-2024
Closing Date: 02-Oct-2024

Location

Kensington, Sydney, NSW

Salary

Starting salary $143007 plus 17% superannuation and leave loading

Responsibilities

Consult and liaise with project leaders, management team, data scientists, education designers and other stakeholders to understand business needs and lead AI system planning, delivery and support.
Collaborate with divisions, faculties and schools to understand their business issues and needs and provide relevant advice or AI solutions that meet their requirements.
Develop, implement, monitor and maintain AI systems using the University approved platforms, managing and optimising data storage and retrieval systems to enable security outcomes.
Provide thought leadership and technical expertise in relation to AI at UNSW.
Design and implement AI models monitoring Azure and AWS resources to ensure AI systems operate in accordance with UNSW standards.
Manage requests and release in DevOps and AI processes.
Provide end-to-end testing support, defining requirements, implementing processes and reporting results.
Provide end-to-end AI System support, responding to requests from stakeholders and implementing solutions.
Create and maintain documentation, including model documentation, systems diagrams and tailored reports as required.
Maintaining and improving AI Systems to ensure technology currency, minimise hallucination model drift and improve performance over time, ensuring that they continue to work as intended.
Identify opportunities for continuous improvement and new projects by investigating and testing new technologies and collaborating with colleagues to evaluate and implement enhancements or new solutions that facilitate improved outcomes for key stakeholders.
Align with and actively demonstrate the Code of Conduct and Values.
Ensure hazards and risks psychosocial and physical are identified and controlled for tasks, projects, and activities that pose a health and safety risk within your area of responsibility.

Requirements

Postgraduate degree in Computer Science, Software Engineering or related field with relevant experience in data engineering, cloud engineering, business intelligence development, or an equivalent level of competency gained through any combination of education, training or experience.
Advanced cloud computing skills and experience in the development and implementation of AI resources and pipelines in cloud-based computing environments.
Advanced programming skills and experience in the implementation and management of structured and unstructured big data analysis. Proven experience in Python and PySpark is highly desirable.
Demonstrated ability to define, develop and implement testing procedures, including knowledge of automated testing software and methodologies.
Demonstrated ability to conduct impact assessments and implement mitigation measures to ensure compliance with cyber and data security and privacy regulations and changes to data collection requirements for the university, identifying ways to collect data in the enterprise systems that protect sensitive data, including research, student and staff data.
Demonstrable high-level problem-solving and analytical skills, to identify and implement required developments and processes to deliver and improve data service solutions.
Demonstrated ability to work proactively and effectively in a collaborative and interdisciplinary environment of teams and stakeholders.
Exceptional communication and interpersonal skills with the ability to build and maintain effective working relationships and convey ideas and information in a clear and professional manner through presentations, written communication, high-quality analysis, submissions, reports and recommendations.
High level organisational and project management skills with experience contributing to large projects in a technical capacity with a wide variety of stakeholders in an agile, deadline-driven environment.
An understanding of and commitment to UNSW’s aims, objectives and values in action, together with relevant policies and guidelines.
Knowledge of health & safety (psychosocial and physical) responsibilities.

Benefits

Career development opportunities
17% Superannuation contributions and additional leave loading payments
Additional 3 days of leave over December/January holiday period
Discounts and entitlements (retail, education, fitness)

Notes

Sponsorship is not available for this role, valid Australian working rights are required on application.
The University reserves the right not to proceed with any appointment.

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Dates

Opening Date: 23-Sep-2024
Closing Date: 07-Oct-2024

Location

Kensington, NSW, Australia

Salary

Level A: $88,290 - $117,718 (plus 17% superannuation and leave loading)

Responsibilities

Collect, wrangle and process data from a variety of sources including open data repository, social media and sensitive data made available to the Housing Analytics Lab project.
Develop and undertake data analytical techniques to understand new insights into city form and function using spatial data, open data, big data and thick data.
Conduct oral presentations relating to the research.
Provide peer review and editing support as a member of the research team and when requested by the Director.

Requirements

PHD or experience in related discipline – data science, modelling and simulation, computer science, geomatics and/or actuarial.
Expertise and skills in data analytical techniques including geoprocessing, spatial-statistics, big data analytics, spatial data mining and data visualisation.
Experience in applying artificial intelligence, machine learning algorithms, national language processing and other data mining techniques to big (ideally city) data.
Advanced computer programming skills in particularly using languages to work with big data including languages such as, python and R.
To be successful you will hold Australian Working Rights or Australian Citizenship. Visa sponsorship is not available for this appointment.

Benefits

Flexible Working Options (work from home, flexible hours etc)
Career development opportunities
17% Superannuation contributions and additional leave loading payments
Additional 3 days of leave over Christmas period
Discounts and entitlements (retail, education, fitness)

Notes

For questions related to the position please contact Persa Tzakis, Interim, Recruitment Manager at p.tzakis@unsw.edu.au.
Applications will not be accepted if sent to the contact listed above.
UNSW reserves the right not to proceed with any appointment.

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Dates

Opening Date: 25-Sep-2024
Closing Date: 27-Oct-2024

Location

Macquarie University, Wallumattagal Campus, North Ryde

Salary

From $106,089 - $113,697 (Level A, Step 6 to Step 8), plus 17% employer superannuation and annual leave loading.

Responsibilities

Lead the development of a low-cost hearing screening device funded by the Cochlear-Macquarie University Joint Fund
Collaborate with leading researchers in hearing science, Cochlear, and mathematicians
Contribute to the development of signal processing and machine learning-based methods to optimize the screening test
Support the research group in developing the next generation of low-cost hearing screening devices
Contribute to other funded projects and help towards implementation of the developed software in hardware devices

Requirements

Hold a PhD in signal processing, machine learning, or a related field such as neuroscience
Experience in signal processing and machine learning
Effective communicator, able to work independently and as part of a team
Keen eye for detail, ensuring high accuracy and data quality
Possess advanced programming skills

Benefits

Access to an active Early Career Researcher support network and professional development opportunities
Work in state-of-the-art research facilities
Significant research, networking, and mentoring opportunities within a highly experienced and supportive research environment
Opportunities to work with several PhD, Masters, and undergraduate students

Notes

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