Fasa University of Medical Sciences

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Australia, Camperdown


	Part time fixed term (0.60 FTE)12 month role at Camperdown-hybrid work arrangement supported
	Be part of a community-led initiative addressing a crucial gap in mental health support for culturally and linguistically diverse (CALD) LGBTQ+ youth in Western Sydney.
	Base Salary $101,318- $116,679 (pro rata for 0.60 FTE)+ 17% superannuation 


About the opportunity

The University of Sydney Susan Wakil School of Nursing and Midwifery (Sydney Nursing School) is the school of choice to nurture global citizens in health and wellbeing. We are currently ranked #1 in Australia and #14 globally in the QS World University Rankings by Subject. Our experienced staff, many of whom work in frontline healthcare services, make a real difference to the healthcare landscape in Australia and internationally.

Sydney Nursing School offers a supportive and collegial environment with many opportunities for professional development. We are committed to providing a workplace that is inclusive and diverse and we encourage applications from suitably qualified and experienced individuals, including women, members of visible minorities, Aboriginal and Torres Strait Islander peoples, and persons with disabilities. Applicants who are willing to embrace our vision and are interested in driving forward our strategy for continuously improving our research impact, student experience, and a respectful, collaborative, culturally safe and person-centred workplace culture are strongly encouraged to apply.

We are seeking a Research Associate to support Dr Horas Wong and the team in a community-led initiative addressing a crucial gap in mental health support for culturally and linguistically diverse (CALD) LGBTQ+ youth in Western Sydney.

This innovative project focuses on developing a multilingual online information hub and a suicide awareness campaign using a co-design methodology. As a Research Associate, you will play a key role in advancing the project's mission to enhance mental health outcomes and reduce stigma around mental health and suicide in this underrepresented community.

Your key responsibilities will be to:


	Conduct needs assessments using both qualitative and quantitative methods to understand the unique mental health challenges faced by CALD LGBTQ+ youth
	collect and analyse data throughout the project's design, implementation, and evaluation phases
	facilitate community consultations to ensure alignment with local needs and priorities
	collaborate with the steering group, youth participants, and community organisations to promote inclusion and participation
	assist in planning and executing the design-a-thon event and related activities
	document activities and support the mentorship process during the design-a-thon
	contribute to the creation of the multilingual online information hub, integrating insights from research and community feedback
	ensure that resources are accessible, culturally relevant, and sensitive to the diverse needs of the target audience
	support impact assessments by analysing user engagement data and gathering feedback from focus groups
	prepare reports and insights to inform future mental health initiatives for diverse populations


About you


	Master's degree in nursing, social sciences, public health, or a related field (or equivalent experience) is required; a PhD is strongly preferred
	proficiency in both qualitative and quantitative research methodologies
	demonstrated strong experience in community-based research or projects focusing on young people, LGBTQ+ individuals, and/or CALD populations is highly desirable.
	a deep understanding of the intersectional challenges faced by CALD LGBTQ+ youth, particularly in the Western Sydney region
	exceptional written and verbal communication skills, including the ability to produce high-quality reports and deliver impactful presentations
	a proven track record of academic publications and presentations is highly preferred
	familiarity with project management tools and methodologies is an advantage


Sponsorship / work rights for Australia

Please note: Visa sponsorship is not available for this position. This role requires valid work rights for Australia.

Pre-employment checks

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.

This position is designated as involving child-related work. To undertake or remain in this position, you are required to apply for and obtain a Working with Children Check clearance in accordance with the Child Protection (Working with Children) Act 2012.

EEO statement

At the University of Sydney, our shared values are trust, accountability and excellence and we strive to be a place where everyone can thrive. We are committed to creating a University community that thrives through diversity and reflects the wider community that we serve. We deliver on this through our commitment to diversity and inclusion, evidenced by our people and culture programs, as well as key strategies to increase participation and support the careers of Aboriginal and Torres Strait Islander People, women, people living with a disability, people from culturally and linguistically diverse backgrounds, and those who identify as LGBTIQ+. We welcome applications from candidates from all backgrounds.

We are proud to be recognised as an Australian Workplace Equality Index (AWEI) Gold employer. Find out more about our work on diversity and inclusion.

How to apply

Please note the University will be closed from 20/12/2024 and will reopen 06/01/2025. We will be interviewing for this role mid January 2025

Applications (including a cover letter, CV, and any additional supporting documentation) can be submitted via the Apply button at the top of the page.

For employees of the University or contingent workers, please login into your Workday account and navigate to the Career icon on your Dashboard. Click on USYD Find Jobs and apply.

For a confidential discussion about the role, or if you require reasonable adjustment or any documents in alternate formats, please contact Cecilia Blamey, Recruitment Operations by email to cecilia.blamey@sydney.edu.au.

Copyright The University of Sydney

The University reserves the right not to proceed with any appointment.

Click to view the Position Description for this role.

Applications Close

Sunday 12 January 2025 11:59 PM


The University of Sydney

Finland

Samuel Kaski’s research group Probabilistic Machine Learning is searching for postdocs to work on AI fundamentals in exciting projects. The work includes collaboration with the Finnish Center for Artificial Intelligence (FCAI), the Centre for AI Fundamentals at the University of Manchester, the Alan Turing Institute, ELLIS and the new ELLIS Institute Finland, and researchers from other fields.

Prof Kaski is Professor of Computer Science in Aalto University and Professor of AI in the University of Manchester. He is Director of Finnish Center for Artificial Intelligence and ELLIS Unit Helsinki. His research group develops machine learning principles and methods focusing on a few key topics (see “Machine learning foundations” below), often working with researchers of other fields in new exciting applications (see the other topics below).

Topics

Machine learning foundations

Keywords: probabilistic modelling, Bayesian inference, simulation-based / likelihood-free inference, multi-agent RL and collaborative AI, sequential decision making and experimental design, privacy-preserving learning, Bayesian deep learning, generative models

We are looking for a new postdoc in the team which develops probabilistic modelling and Bayesian inference methods. The team has several exciting new machine learning formulations we work on, and opportunities for applying the methods with top-notch collaborators. The core is always development of new methods, and with this call we are looking for talented researchers with background in machine learning, stats or CS (or other directly relevant topics) who are keen on developing the new methods. In the cover letter, let us know what you are interested in - if we are already working on it, all the better, but we are willing to listen to new ideas too.

Machine learning for synthetic biology and biodesign

Keywords: AI-based design, human-in-the-loop machine learning, collaborative AI, molecular modeling, graph neural networks, deep learning algorithms, generative models

We are searching for early career scientists to join our research team working towards next-generation machine learning methods for synthetic biology. The positions are available in two large multi-year projects (BIODESIGN and BIOFOUNDRY) focused on establishing virtual laboratories for protein engineering and biomanufacturing, implemented in collaboration between FCAI and VTT Technical Research Centre of Finland, and NSF Global Center on biofoundries. The aim of the projects is to design novel AI-based tools for bioengineering. These tools will combine cutting edge machine learning techniques, such as graph neural networks, deep generative models, Bayesian optimization, and human-in-the-loop learning with the synthetic biology expertise of VTT. The virtual laboratories are envisioned to have a wide range of applications in industry (e.g., new biochemicals, biomaterials and drugs), and to help the transition to a carbon-neutral society.

Applicants should have a strong academic record in computer science, mathematics, or statistics. Solid research experience in one or more of the following fields is beneficial: AI-based design, Deep learning algorithms, Generative models, Human-in-the-loop machine learning, Collaborative AI, Molecular modeling, Reinforcement learning, Structured prediction.

The successful applicants will join a world-class research team with top AI researchers from FCAI and synthetic biology experts from VTT.

Real-time AI-assistance with computationally rational user models

Keywords: collaborative AI, human-in-the-loop ML/RL, reinforcement learning, user modelling

Despite recent advances in AI and machine learning, there are few AI solutions that can be applied when we cannot precisely specify the objective or do not have suitable data to learn from. This is particularly salient and challenging in ad hoc assistance for human users in complex tasks such as scientific discovery. 

This project aims to address this issue by learning these objectives, and to assist, directly from interaction with the users. To do so, we develop reinforcement learning techniques for AI-assistants and computationally rational user models that take into account factors such as cognitive biases to reason about human decision-making. We push state-of-the-art in AI that, through inference over - and planning with - such user models, is able to tackle problems that are otherwise out of reach of mainstream AI solutions. 

Supported by a High-performance computing grant from the Research Council of Finland, we are looking to strengthen this team with postdocs with a strong academic record in computer science, mathematics, or statistics. Solid research experience in one or more of the fields listed under this topic is beneficial.

Team: this project will be carried out with a top expert on computational rationality, Prof. Andrew Howes of University of Exeter,  and experts in application domains.

Next generation distribution shifts

Keywords: distribution shift, out-of-distribution generalization, robust deployment, deep learning, experimental design

Robust algorithms for machine learning models are vital as the deployed scenario can differ from the training scenario in unexpected ways. Placing assumptions on the kind of distribution shift we expect, such as covariate or label shift, and accounting for it during training is common practice. However, these assumptions are often too restrictive for real-world settings, as the shifts encountered are typically more complex. Moreover, it is difficult to know a priori which shifts we need to account for. This project focuses on developing novel machine learning methods  that demonstrate robust performance by adapting to unforeseen shifts and diverse datasets during deployment.

We are looking for applicants with a strong academic record in computer science, mathematics, or statistics. Solid research experience in one or more of the following fields is beneficial: distribution shift, out-of-distribution generalization, out-of-domain generalization, sequential experimental design.

Your experience and ambitions

We expect the candidates to hold or be close to getting a relevant doctoral degree and have a solid background in the mathematics/statistics/computer science needed in machine learning.

Previous experience in the application fields is an advantage. Capability of both independent work and teamwork, and excellent written and spoken English are necessary.

What we offer

We provide

RESEARCH ENVIRONMENT

You will work in Professor Samuel Kaski’s research group (Probabilistic Machine Learning Group). We design collaborations as we go, according to what the research needs. Collaborators include but are not restricted to the other groups in the Finnish Center for Artificial Intelligence (FCAI), other sites of the European Laboratory for Learning and Intelligent Systems (ELLIS) and our new ELLIS Institute Finland, Centre for AI Fundamentals of the University of Manchester, the Turing Institute, and a number of excellent researchers in other fields in our applications. 

JOB DETAILS

Postdoc positions are typically made for up to three years. Starting dates are flexible. All positions are negotiated on an individual basis. We are strongly committed to offering everyone an inclusive and non-discriminating working environment. We warmly welcome qualified candidates from all backgrounds to apply and particularly encourage applications from women and other groups underrepresented in the field.

All our positions are fully funded and the salary is based on the Finnish universities’ pay scale. The starting salary depends on the level of the position and the previous experience and is typically increased as the experience grows. All employees have access to the occupational health care services and are covered by the Finnish national health insurance system.

Ready to apply?

Submit your application through our recruitment system Workday by the link below. The deadline for applications is  February 2 2025 at 23:59 Finnish time, 2024.

Required attachments


	Cover letter (1–2 pages). 
	CV
	List of publications (please do not attach full copies of publications)
	A transcript of doctoral study
	The degree certificate of your latest degree. If you don’t yet have a PhD degree, a plan of completion must be submitted.
	Contact details of two senior academics who can provide references. We will contact your referees if we need recommendation letters.


All materials should be submitted in English in a PDF format. Note: You can upload max. five files to the recruitment system, each max. 5MB.

Please note: Aalto University’s employees should apply for the position via our internal system Workday -> find jobs (not external aalto.fi webpage on open positions) by using their existing Workday user account.

Contacts: Coordinator Fang Wang (fang.wang@aalto.fi)

More Information

We are part of Finnish Centre for Artificial Intelligence FCAI and ELLIS Unit Helsinki. More information on their pages, and the frequently asked questions on this page.  

Aalto University (53rd in the Times Higher Education THE ranking list of most international universities in the world) is a community of bold thinkers where science and art meet technology and business. We are committed to identifying and solving grand societal challenges and building an innovative future. Aalto has six schools with nearly 12 000 students and a staff of more than 4000, of which 400 are professors. Our main campus is located in Espoo, Finland. Diversity is part of who we are, and we actively work to ensure our community’s diversity and inclusiveness. This is why we warmly encourage qualified candidates from all backgrounds to join our community.

The Department of Computer Science is an internationally-oriented community and home to world-class research in modern computer science, combining research on foundations and innovative applications. With over 40 professors and more than 450 employees from 50 countries, it is the largest department at Aalto University and the largest computer science unit in Finland. Computer science research at Aalto University ranks high in several prominent surveys (47th worldwide and 9th in Europe in Shanghai subject ranking 2019; and 56th worldwide in Times Higher Education subject ranking 2020).

About Finland

Finland is a great place for living with or without family – it is a safe, politically stable and well-organized Nordic society. Finland is consistently ranked high in quality of life and was just listed again as the happiest country in the world: https://worldhappiness.report/news/its-a-three-peat-finland-keeps-top-spot-as-happiest-country-in-world/. For more information about living in Finland: https://www.aalto.fi/services/about-finland

More info:

twitter.com/fcai_fi
linkedin.com/company/fcai
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Newsletter: http://eepurl.com/gVPBpf

Aalto.fi 

twitter.com/aaltouniversity 
facebook.com/aaltouniversity
instagram.com/aaltouniversity

More about Aalto University:

Aalto.fi
youtube.com/user/aaltouniversity
linkedin.com/school/aalto-university/
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Aalto University

Australia, Melbourne

We are seeking a highlight motivated and experienced Course Coordinator to lead the development of a Graduate Diploma in Early Childhood Education. The ideal candidate will be a visionary academic leader with a deep commitment to early childhood education, possessing the expertise to design, develop, and implement a robust curriculum that meets the highest standards of excellence. This leadership role involves academic management, program development, accreditation processes, and fostering partnerships within and beyond the education sector.

About Harrow Institute:

Harrow Institute is a forward-thinking and innovative private education provider committed to delivering exceptional graduate and postgraduate education in Australia.

Key Responsibilities:

Curriculum Development: Lead the development of a comprehensive and innovative curriculum for the Graduate Diploma in Early Childhood Education, ensuring alignment with industry standards and accreditation requirements.

Academic Leadership: Provide academic leadership, including the mentorship of academic members, overseeing academic quality, and fostering an environment of research and learning.

Accreditation and Compliance: Navigate the accreditation process with relevant bodies, ensuring the program meets all regulatory standards and requirements for early childhood education in Australia.

Stakeholder Engagement: Engage with stakeholders including industry partners, community organisations, and academic institutions to enhance the program's relevance and impact.

Scholarship and Innovation: Encourage and lead scholarship initiatives related to early childhood education, contributing to the body of knowledge and the institute's reputation.

Student Success: Foster a supportive and inclusive learning environment that promotes student success, retention, and graduate outcomes.

Core selection criteria:

Education: A PhD in Early Childhood Education from an accredited institution or a PhD candidate in Early Childhood Education with substantial experience in academia.

Experience: At least three years of academic management experience within the higher education sector specialised in Early Childhood Education in Australia, with a proven track record in program development and leadership.

Skills: Exceptional leadership, communication, and organisational skills; a deep understanding of early childhood education principles and practices; familiarity with accreditation processes and requirements in Australia.

Attributes: A visionary leader with a passion for education innovation, a commitment to excellence, and an ability to inspire others.  

How to Apply:

Please submit your application including a cover letter, CV, and a statement addressing the key selection criteria outlined in this position description. Applications should be sent to harrow@lizlegal.com.

Application Deadline: 20 January 2025

Harrow Institute is an equal opportunity employer and strongly encourages applications from diverse candidates, including those with different levels of experience, and from all sections of the community.

Applicants must hold a valid visa to work in Australia.


Harrow Institute

Australia, Adelaide


	Based in the UniSA Allied Health and Human Performance unit at the City West campus
	Part-time (0.8 FTE), fixed term contract until 15 January 2027
	Salary: $100,322 - $133,388 (pro rata) per annum (plus 17% superannuation)


About the Role

The Research Associate or Fellow will investigate the roles of human endogenous retrovirus (part of human genome sequences) on motor neuron disease. In this position, you will conduct research activities primarily through statistical genetic analysis of large-scale multi-omics data on motor neuron disease. This position will offer the opportunity to work at all levels of research from establishing research questions through to publishing high quality research outputs.

About UniSA

The University of South Australia is Australia’s University of Enterprise. Our culture of innovation is anchored around global and national links to academic, research and industry partners. Our graduates are the new urban professionals, global citizens at ease with the world and ready to create and respond to change. Our research is inventive and adventurous and we create new knowledge that is central to global economic and social prosperity.

Allied Health and Human Performance

At UniSA Allied Health and Human Performance, we shape community wellbeing by educating future health professionals, producing graduates who contribute to the future health workforce. We deliver solutions-based research that addresses global health needs, working with industry and the community to solve critical health challenges. 

Core Responsibilities


	Contribute to research planning by participating in sessions, offering ideas, reviewing literature, writing papers, and attending seminars
	Contribute to research execution by managing and analysing data, exploring new methods, seeking information from various sources, and assessing resource requirements
	Contribute to disseminating knowledge by drafting reports and papers, and attending meetings and conferences
	Contribute to the preparation and development of grant and tender applications, including undertaking power calculations, literature searchers, and other tasks as required
	Contribute to the supervision of Honours, Masters and PhD students, as required


Essential Skills and Experience  

Level ARAS 


	Postgraduate qualifications in a relevant field (e.g., quantitative genetics, statistics, bioinformatics, computer programming, epidemiology)
	Knowledge and understanding of statistical genetics and experience with the analysis of complex traits
	Experience in computer programming, including working with databases and handling large data files
	A developing research record demonstrated by publications, conference papers, and other research activities
	Strong verbal and written communication skills, with the ability to present information clearly to diverse audiences and work collaboratively in a multidisciplinary team


Level BRF


	PhD in a relevant field (e.g., quantitative genetics, statistics, bioinformatics, computer programming, epidemiology) with postdoctoral research experience
	Demonstrated knowledge and extensive experience in statistical genetics and the analysis of complex traits
	Proficiency in computer programming, including database communication and handling large data files
	An evolving research record with publications, conference papers, and other research activities
	Strong verbal and written communication skills, with experience in presenting information to diverse audiences and working collaboratively in multidisciplinary teams, alongside high-level problem-solving and organizational abilities


Benefits

Getting a great job working with the best is just the start. UniSA rewards its staff with a wide variety of benefits such as:


	Generous superannuation contributions of 17%
	Flexible working conditions
	Employee assistance and development programs
	A range of salary packaging options, including vehicle leasing, laptops and car parking fees
	Various on-site services available at our campuses which may include on-site gym membership


Culture

At the University of South Australia, we value workplace diversity and are committed to providing a supportive, inclusive, and respectful work environment for all people. We strongly encourage applications from Aboriginal and Torres Strait Islander Peoples, women, members of the LGBTIQ+ community, people of culturally diverse backgrounds and people with disability.  

Start Your Unstoppable Career!  

For a copy of the position description and to apply, please visit Working at UniSA. The online application form will list the specific selection criteria that you need to address.  

Please address your cover letter to Laura Gomes, Consultant: Recruitment Central. For further information about the position or the recruitment process, please contact UniSA Recruitment Central on +61 8 8302 1700 or via email at recruitment@unisa.edu.au using job reference number 6854. 

Applications close: 11:30pm Sunday 12 January 2025

We are committed to providing an equitable and barrier free recruitment process and encourage you to share any support, adjustments and/or access requirements you have by contacting our Recruitment Central team on recruitment@unisa.edu.au. Anything you tell us will be kept completely confidential.  

Applications welcomed from Australian or NZ citizens, Australian permanent residents and those who have the legal right to work in Australia for the term of appointment. 

CLICK HERE for Position DescriptionOpens in new window

How to apply:a


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Applications must be lodged online, please note UniSA does not accept applications via email.


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UniSA is committed to developing a diverse workforce and a constructive enterprising culture in which everyone can thrive.

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University of South Australia

Singapore

As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets that are relevant to industry demands while working on research projects in SIT.

The primary responsibility of this role is to deliver on an applied research project as a part of Infocomm Technology cluster at SIT. In this role, you will be part of the research team, working to develop and evaluate privacy-preserved Generative AI algorithms for generating synthetic Personal Identity Information (PII). This aims to overcome the issues raised by using real-world PII data.

Key Responsibilities:


	Participate in and manage the research project with the Principal Investigator (PI), Co-PI and the research team members to ensure all project deliverables are met.
	Design a Natural Language Processing algorithm for identifying Personal Identity Information data.
	Design and evaluate privacy preserved Generative AI-based algorithm for generating synthetic data.
	Validate integrated system functionality and performance.
	Help produce progress reports and technical papers on research work.
	Ensure compliance with Work, Safety and Health Regulations.
	Assist in project resource requirements and managing student projects.


Job Requirements:


	Have a PhD Degree in Computer Engineering/Computer Science/Electrical Engineering or equivalent.
	Have relevant research/industry experience in Machine Learning, AI and Privacy.
	An excellent team player who can cope with an agile and fast-paced environment.
	Good communication and interpersonal skills.
	Possess relevant hands-on experience in Python, Java, C++ etc. and corresponding development environments.  



Fasa University of Medical Sciences

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