Nile University of Nigeria

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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

$122,830 - $145,858 p.a. + 17% superannuation


	Full time, continuing position. Located at the Faculty of Science on the Camperdown Campus
	Exciting opportunity for a Lecturer to join the School of History and Philosophy of Science
	Base Salary Level B, $122,830 - $145,858 p.a. + 17% superannuation 


About the opportunity

The School of History and Philosophy of Science is seeking a Lecturer in History and Philosophy of Science (HPS) for a full time, continuing position.

The successful candidate's teaching duties will include the history of science or medicine in Asia or the Pacific, with the ability to address problems in the global history of knowledge.

About you

The University values courage and creativity; openness and engagement; inclusion and diversity; and respect and integrity. As such, we see the importance of recruiting talent aligned to these values and are looking for a Lecturer in History and Philosophy of Science (HPS) who has:


	a PhD and publications in relevant fields
	research interests in the history of science or medicine
	we particularly welcome applications from scholars who engage with connections and exchange or knowledge practices across traditions and regions.


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.

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 address the selection criteria in your application (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.

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

Thursday 20 February 2025 11:59 PM


China, Ningbo

Department of Electrical and Electronic Engineering at University of Nottingham Ningbo China is seeking outstanding Research Fellows in Electronic Engineering (OUTSOURCED) to join Industrial Joint-Lab on Smart Mobility and Transportation.

Your Responsibility

The purpose of this role is to conduct cutting-edge research on 5G/6G technologies and their integration with smart transportation systems, with a focus on C-V2X applications.


	Formulating research questions and objectives towards the development of research programme for both the lab and industrial partners. This includes the establishment of methodologies and techniques to effectively conduct research within the specified area.
	Conducting research, which includes developing models, testbeds, conducting experiments, and performing analyses, all while adhering to project deadlines and collaborating seamlessly with team members and partners.
	Demonstrating successful research outputs by publishing in high-impact journals and presenting at top international conferences.
	Identifying opportunities and assisting senior staff members in writing bids for research grant applications at both national and international levels.
	To participate in training and staff development events as trainer or trainee as appropriate.
	To maintain appropriate professional development, expertise and awareness.
	To undertake other tasks and responsibilities as may reasonably be required.


About You


	PhD in relevant subject areas;
	Proven track record in high quality journals and conferences publications;
	Practical experience of applying the specialist skills and techniques required for the role;
	Good oral and written communication skills in English, including the ability to communicate with clarity on complex information. Excellent communication skills in Chinese is a plus.


About Us

Join a unique British University in China. The University of Nottingham Ningbo China (UNNC) was the first Sino-foreign university to open its doors in China. This award winning campus offering a UK style education has grown to establish a student body of over 9,000 in just 20 years.

About Industrial Joint-Lab on Smart Mobility and Transportation

The primary aim of this laboratory is to develop innovative technologies that address the growing complexities and demands of modern urban mobility. Through pioneering research and development, the lab seeks to create solutions that are adaptable, scalable, and capable of improving urban transportation systems.

In close collaboration with industry partners, the laboratory focuses on enhancing traffic safety, efficiency, and sustainability. This includes developing state-of-the-art communication protocols, sensor technologies, and AI-driven decision-making systems that empower smarter mobility infrastructure. A core emphasis lies in advancing autonomous driving technologies and connected autonomous vehicles (CAVs) to enable seamless vehicle-to-everything (V2X) communication.

By integrating these technologies, the lab aims to reduce road accidents, optimise traffic flow, and mitigate congestion in increasingly dense urban environments. The research also explores the deployment of resilient and adaptive systems that can handle real-time data from complex environments, enabling CAVs to make instantaneous and accurate decisions.

Additionally, the lab addresses the broader ecosystem of urban mobility, including eco-friendly solutions and sustainable transportation models that align with smart city initiatives. This comprehensive approach ensures that the technologies developed not only meet current mobility challenges but also anticipate future demands, facilitating safer, greener, and more efficient urban transport networks.

Key Areas:

5G and beyond C-V2X Technologies: Enhance vehicle-to-infrastructure (V2I) communication for road safety, traffic efficiency, and autonomous driving.

Smart Sensors and Autonomous Systems: Develop advanced sensors and AI integration for improved vehicle localisation, obstacle detection, and real-time environmental perception.

Connected and Autonomous Vehicles (CAVs): Advance CAV technologies to optimise traffic management, reduce congestion, and improve road safety.

Sustainable Urban Mobility Solutions: Research eco-friendly transportation, such as electric public transport, to promote sustainable urban mobility.

The target breakthrough includes cutting-edge technologies for smart mobility, including C-V2X communication, smart sensors, and AI-driven autonomous systems. These technologies will reduce traffic congestion, enhance road safety, and support the deployment of autonomous vehicles, contributing to sustainable and efficient urban mobility solutions.

Your Remuneration, Benefits and Support

You will be offered a fixed term outsourced contract initially with effect from February 2025 or as soon as thereafter. We are committed to providing competitive employment packages while supporting the wellbeing of our staff to help them reach their full potential.

How to Apply

Applicants should submit an application via our on-line application system before 17 January 2025. Only on-line applications will be accepted. Referees will be contacted prior to interview and interviews will take place in Ningbo China.

Applications should include but are not limited to the following:


	A cover letter
	An up-to-update CV includes academic and research achievement list
	A Research proposal  


Enquiries

Informal enquiries regarding the research project may be addressed to Dr C.F. Kwong (Chiew-Foong.Kwong@nottingham.edu.cn) or Dr David Chieng (David.Chieng@nottingham.edu.cn). If you are unable to apply on-line please contact the Human Resources Office, Tel: 86 574 88180000(Ext. 8404).


University of Nottingham Ningbo, China

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
youtube.com/channel/UC7nUhposDgxzDOKns_H5J0w
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/
www.facebook.com/aaltouniversity
instagram.com/aaltouniversity
twitter.com/aaltouniversity


Aalto University

Australia, Geelong


	Based at our Geelong, Waurn Ponds Campus
	Part-time 0.6FTE and fixed-term for 2 years
	Level A $76,985 - $103,493 + 17% Superannuation (pro rata, part time)


Who are we?

Deakin University stands as a shining beacon of excellence in the world of higher education.  Deakin is renowned for its unwavering commitment to innovation, research, and inclusivity. With a strong emphasis on cutting-edge research and a diverse, globally-connected community, Deakin provides an unparalleled educational experience. Here, students not only gain knowledge but also develop the skills and mindset needed to thrive in a rapidly evolving world. Discover the thrill of intellectual exploration and let Deakin's passion for learning and innovation ignite your own, as you prepare to shape the future with confidence and purpose.

The Faculty of Health is dedicated to being at the forefront of teaching, learning, creating and social development and fostering cutting-edge research and discovery. The School of Medicine places high emphasis on research that makes a difference and is solution-led. We work closely with industry partners and the government to put findings into practice.

The associate lecturer will contribute academic to the delivery of the anatomy and pathology practical program in the School of Medicine. They will work with other team members to facilitate student learning of anatomy and pathology across the schools’ programs. The appointee will promote the Faculty within the academic and professional communities in Australia, contributing to the Faculty’s teaching and program development initiatives. The appointee will liaise with students at all levels.

As Associate Lecturer in Medical Science, you will:


	Assist in applying discipline knowledge into student learning experiences to support success and engagement.
	Support innovation in curriculum design and deliver learner-centric, research-informed teaching practices across different levels / modes of delivery.
	Maintain deep discipline knowledge which is applied to inform curriculum design.
	Facilitate collaborative learning opportunities for students and provide academic mentoring and support
	Assist course teams in integrating new pedagogical research across all aspects of education.


To be successful, you’ll have: 


	PhD in a relevant discipline and/or other relevant qualifications and experience
	Demonstrated knowledge of anatomy and pathology and its delivery in an educational setting
	Excellent record of scholarly learning and teaching in UG and/or PG programs.
	Demonstrated capacity and passion for teaching, research and facilitation of student learning.
	Demonstrated capacity to provide academic support and guidance to students, ensuring an inclusive and positive learning environment.


Here's how to apply: 

Please submit your updated resume, a short cover letter and responses to the Key Selection Criteria.

For a confidential discussion regarding this role, please contact Janet McLeod, Associate Head of School (Learning and Teaching) on janet.mcleod@deakin.edu.au

Please note, Deakin university is closed for the Christmas period from Monday 23 December 2024 to Wednesday 1 January 2025 inclusive.

For a copy of the position description, please see below:  PD - Associate Lecturer in Medical Science.pdf

Applications for this position close 11.55pm on Monday 20 January 2025.

Why work with us?

At Deakin you will have access to benefits such as a variety of leave options including generous parental leave and the ability to purchase additional leave; flexible working arrangements to help manage your work-life balance; ongoing learning and development opportunities to grow your career; an inclusive and supportive culture and environment to work in, both online and on campus.

Are You Ready?

Deakin is a Victorian university with a global impact. We are an agile, dynamic, and innovative university committed to making a positive impact through our excellence in education, research and innovation and the contributions we make to the wider community.

We understand that our reputation has been built on the dedication and expertise of our staff and we offer a dynamic and diverse working environment with opportunities to grow and develop careers. We believe that a progressive, thriving culture will ensure that people choose to come, and stay at Deakin and contribute to our ongoing success.

We value diversity and aim to build an inclusive environment that champions, embraces and respects differences. We support and encourage applications from Aboriginal and Torres Strait Islander people, and people of all abilities, cultures, sexual orientation, and genders.


Nile University of Nigeria

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