Gregory University Uturu

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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


	Preview Application FormOpens in new window


Applications must be lodged online, please note UniSA does not accept applications via email.


	Start your application by clicking the ‘BEGIN’ button
	If you have already registered for an account, please login before starting your application
	If you have forgotten your log in details, click here to reset your password
	You will be able to save your progress throughout your application


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

United Kingdom, Glasgow

Closing date: 03/02/2025
Salary range: £36,924 - £45,163 (Pro Rata)
FTE: 0.8 (28 hours/week)
Contract Type: Fixed Term (18 months)

The Department of Psychological Sciences and Health is recruiting a Research Associate to work with Dr Dwight Tse on the ESRC-funded project “A Comprehensive approach to enhance Older adults' Preparedness for Extreme temperatures (COPE)”. This is a joint project with researchers at University of Exeter and international collaborators (e.g., Canada, Hong Kong, Israel, Sweden) to enhance older adults' preparedness for extreme heat by co-developing localised adaptation and mitigation strategies with community partners, integrating their lived experiences to improve health, safety, and well-being. This post is available on 01 May 2025 (start date is flexible), for a fixed term of 18 months.

As a Research Associate, under the general guidance of Dr Dwight Tse, you will develop research objectives and proposals, play a lead role in relation to a specific project/s or part of a broader project, conduct individual and/or collaborative research, contribute to the development of new research methods, identify sources

For informal enquiries, please contact Senior Lecturer in Psychology, Dwight Tse (dwight.tse@strath.ac.uk)

please click here for further details.pdf


University of Strathclyde

Singapore

FACULTY OPENING FOR NURSING AT THE SINGAPORE INSTITUTE OF TECHNOLOGY

The Singapore Institute of Technology (SIT) is Singapore’s first University of Applied Learning, offering industry-relevant degree programmes that prepare its graduates to be work- and future-ready professionals. Its mission is to maximise the potential of its learners and to innovate with industry, through an integrated applied learning and research approach, so as to contribute to the economy and society.

The university’s unique pedagogy integrates clinical practice education and academic endeavour, embracing authentic learning in a real-world environment through collaborations with key strategic partners. Its focus on applied research with clinical impact is aimed at helping the healthcare and social services sector innovate and grow.

SIT espouses an applied learning approach and offers degrees with a strong focus on science and technology. Our faculty work closely with industry on translational research and innovation, as well as provide consultancy on solutions to industry challenges.

As a young university, we encourage innovation and seek the right candidates to join us in realising our vision. We offer competitive remuneration, generous employment benefits, access to funding to undertake research of relevance to industry, and opportunities to inspire and nurture the next generation of skilled and work-ready graduates. We currently have positions available at all levels, from Lecturer to Full Professor, for the discipline- Nursing in the Health and Social Sciences Cluster.

Applicants should possess:


	an earned PhD in Nursing from a reputable university,
	a nursing practitioner license,
	extensive experience in:
	
		teaching nursing courses to students or professionals
		research work in the field of healthcare, particularly in nursing
		publication in nursing services and/or clinical research. 
	
	


The appointee will be expected to undertake funded clinical-relevant research and teach courses in healthcare and nursing.

Applications will be accepted until the positions are filled. All applications must be submitted electronically via the "Apply Now" button below. Please contact the HSS Cluster Director, Associate Professor Tan Bhing Leet via HR_Faculty@singaporetech.edu.sg if you have any enquiries relating to these opportunities. 


Singapore Institute of Technology (SIT)

United Arab Emirates, Abu Dhabi

Description

The Healy Laboratory in the Chemistry Program of the Division of Sciences at New York University Abu Dhabi seeks to recruit a Post-doctoral Associate starting September 2025. Applicants with backgrounds in synthetic organic and medicinal chemistry are encouraged to apply. The research is aimed at developing an automated chemical platform for the synthesis and biological evaluation of natural products as leads for a drug discovery program. The lab and the core research facilities at NYUAD are equipped with state-of-the-art facilities for organic synthesis (https://healylab.com/).  

Applicants must have received a Ph.D. in chemistry or related subject or be within a few months from completion. We encourage applications from candidates with significant research experience in the synthesis of complex molecules, particularly polyketides. Knowledge of synthetic automation/chemical engineering, biosynthesis or chemical biology is desired, but not required. Excellent communication skills in English, ability to work in multi-disciplinary teams, and scientific creativity are essential.

The terms of employment include highly competitive salary, housing allowance and educational subsidies for children. Applications will be accepted immediately and candidates will be considered until the position is filled. To be considered, all applicants must submit a cover letter which describes your motivation to join the Healy Laboratory, a curriculum vitae with full publication list, a one-page summary of research accomplishments and interests, a transcript, and two letters of recommendation, all in PDF format. If you have any questions, please e-mail alan.healy@nyu.edu.

About NYUAD

NYU Abu Dhabi is a degree-granting research university with a fully integrated liberal arts and science undergraduate program in the Arts, Sciences, Social Sciences, Humanities, and Engineering. NYU Abu Dhabi, NYU New York, and NYU Shanghai, form the backbone of NYU’s global network university, an interconnected network of portal campuses and academic centers across six continents that enable seamless international mobility of students and faculty in their pursuit of academic and scholarly activity. This global university represents a transformative shift in higher education, one in which the intellectual and creative endeavors of academia are shaped and examined through an international and multicultural perspective. As a major intellectual hub at the crossroads of the Arab world, NYUAD serves as a center for scholarly thought, advanced research, knowledge creation, and sharing, through its academic, research, and creative activities.

EOE/AA/Minorities/Females/Vet/Disabled/Sexual Orientation/Gender Identity Employer

UAE Nationals are encouraged to apply.

Equal Employment Opportunity Statement

For people in the EU, click here for information on your privacy rights under GDPR: www.nyu.edu/it/gdpr

NYU is an equal opportunity employer committed to equity, diversity, and social inclusion.


New York University Abu Dhabi Corporation

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 

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More about Aalto University:

Aalto.fi
youtube.com/user/aaltouniversity
linkedin.com/school/aalto-university/
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