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Polytechnic of Guarda

Guarda is the highest and oldest city in Portugal. The former fortress town is home to the Polytechnic of Guarda, which was founded in 1980. In its four schools spread across three campuses are more than 250 teaching staff looking after about 3,000 students on its 25 bachelor’s and 15 master’s programmes. It has international links with institutions in Brazil and France. 
The polytechnic is involved in research and community service. It has a strong commitment to regional development, and it has established a Research Unit for Inland Development to support this mission. 
The Polytechnic of Guarda is near the spectacular Serra da Estrela Nature Park, a major tourist attraction and destination for nature lovers and adventurers. 

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United Kingdom, Southampton

The University of Southampton with support from the UKRI is funding until 30/09/2027 full-time work on the use of data assimilation for turbulent flows.

You will be working under the supervision of the UKRI Future Leaders Fellow Prof Christina Vanderwel on the project “Simulating air pollution in the lab”. The aim of this research is to apply novel data assimilation techniques to reconstruct wind patterns and air pollution in urban areas. Data driven methods will build on experiments conducted in the University of Southampton’s wind and water tunnel facilities using state-of-the-art laser diagnostics. The candidate will use discrete adjoint libraries in OpenFOAM to improve turbulence modelling of environmental flows. There will also be opportunities to get involved in other projects in experimental fluid mechanics including turbulent boundary layers, flow control, atmospheric flows, and diagnostics development. 

You will join a large and friendly aerodynamics group (http://www.southampton.ac.uk/engineering/research/groups/afm.page) engaged in a wide range of experimental and numerical studies of turbulent flows. The AFM research group is comprised of experts in theoretical, computational and experimental fluid mechanics and our aim is to provide an environment in which these different approaches can be combined and focused on particular topics of practical importance. You will join a vibrant and supportive team of other postdoctoral researchers and graduate students working in different areas of fluid mechanics ranging from environmental flows to biomedical applications. 

To be successful you will have a PhD or equivalent qualifications and experience in data-driven fluid mechanics and turbulence.

Please contact Dr Christina Vanderwel (C.M.Vanderwel@soton.ac.uk) for further details about the position. 

Equality, diversity and Inclusion is central to the ethos in the School of Engineering. We particularly encourage women, Black, Asian and minority ethnic, LGBT and disabled applicants to apply for this position. In recognition of our continued commitment to improving equality for women in science we were awarded an Athena SWAN bronze in 2013 and 2016. We give full consideration to applicants that wish to work flexibly including part-time and due consideration will be given to applicants who have taken a career break. 

The University of Southampton is in the top 1% of world universities and in the top 10 of the UK’s research-intensive universities. The University of Southampton is committed to sustainability and being a globally responsible university and has recently been awarded the Platinum EcoAward. Our vision is to embed the principles of sustainability into all aspects of our individual and collective work, integrating sustainable development into our business planning, policy-making, and professional activities. This commits all of our staff and students to take responsibility for managing their activities to minimise harm to the environment, whether this through switching off non-essential electrical equipment or using the recycling facilities.

Working at the University of Southampton:

Check out the staff benefits and why you should join us at The University of Southampton.


University of Southampton

Australia, Camperdown


	Part-time or full time continuing role at Westmead and Sydney Dental Hospital
	Lecturer Clinical Education in Dentistry -Tooth Conservation Discipline
	Base Salary $127,436- $151,328+ 17% superannuation + dental loading (pro-rata)


About the opportunity

The University of Sydney School of Dentistry (Sydney Dental School) is ranked amongst the top dental schools internationally and is one of the largest dental schools in Australia. It has campuses in the Sydney Dental Hospital (in inner-eastern Sydney), the Westmead Centre for Oral Health at Westmead Hospital (in western Sydney), the Nepean Centre for Oral Health and outreach service-based teaching is undertaken across the state of NSW.

We are seeking a Lecturer in Tooth Conservation to deliver clinical education within our integrated clinics.

Your key responsibilities will be to:


	undertake independent teaching and assessment and apply research or scholarly activity to enhance educational practices and outcomes
	deliver high-quality teaching and learning experiences that meet the university's standards for education
	develop innovative teaching approaches and evaluate effectiveness for continuous improvement
	conduct original research independently or collaboratively, with a focus on publication, conference presentations, and securing research funding
	coordinate academic staff activities and provide training and mentorship to less experienced lecturers
	carry out administrative tasks and actively contribute to faculty or school meetings
	foster a positive workplace culture that values diversity of thought, collaboration, excellence, and achieving outcomes
	understand and contribute to advancing the university and faculty/school strategic agenda
	build a professional profile through participation in conferences, seminars, and outreach activities
	engage in translational research and establish collaborations for research, development, commercialisation, and policy improvement
	undertake other duties and contribute to projects appropriate within the classification level as required


About you


	AHPRA registration
	bachelor degree in the field of dentistry
	postgraduate qualifications in dentistry and /or an equivalent combination of relevant training and experience
	PhD in a relevant discipline (optional)
	clinical experience in the discipline of tooth conservation or general dental practice
	experience conducting original research and engaging in scholarly activity
	a developing network of academic, industry and professional partners and stakeholders
	a developing research profile in discipline or area of expertise
	proven experience in teaching and learning within an established programme and in a variety of settings
	proven experience in designing, implementing and evaluating teaching and learning initiatives
	demonstrated success in implementing and evaluating teaching and learning initiatives with a clinical and patient care focus (desirable)


Sponsorship / work rights for Australia

You must have unrestricted work rights in Australia for the duration of this employment to be eligible to apply. Visa sponsorship is not available for this appointment.

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.

As this position is located on an NSW Health site, it is a regulatory requirement to complete compulsory employment checks prior to starting in this position. For more information and instructions, please visit: NSW Health employment requirements

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 LGBTQIA+. We welcome applications from candidates from all backgrounds.

We are proud to be recognised as an Australian Workplace Equality Index (AWEI) Platinum Employer. Find out more about our work on diversity and inclusion.

How to apply

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.

© 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

Monday 05 January 2026 11:59 PM


The University of Sydney

We are seeking a highly motivated and skilled Research Fellow to join the Cancer Data-Driven Detection (CD3) programme. CD3 is a new, multidisciplinary and multi-institutional strategic national research programme dedicated to using data to transform our understanding of cancer risk and enable early interception of cancers. It represents a major, multi-million-pound flagship investment funded through a strategic programme award by Cancer Research UK, the National Institute for Health and Care Research (NIHR), Engineering and Physical Sciences Research Council (EPSRC), and the Peter Sowerby Foundation; in partnership with Health Data Research UK (HDR UK) and the Economic and Social Research Council’s Administrative Data Research UK programme (ADR UK).”

The post-holder will play a central part in CD3’s effort to develop next-generation cancer risk models. Working within the advanced analytics workstream, they will bring together electronic health records, administrative datasets, and emerging multi-omic measurements to build and test machine-learning-based multimodal risk prediction tools. A key element of the role will be to explore how different data types and AI-derived features can contribute to risk, identify robust and clinically meaningful signals, and work closely with collaborators across the programme to ensure models are transparent, reliable and suitable for real-world use. The position offers the opportunity to shape core analytical methods used across CD3 and to contribute to one of the largest coordinated efforts in the UK to transform early cancer detection through data.

The post will be based in the School of Biological Sciences in Southampton but will involve co-mentoring and close collaboration with investigators across multiple institutions, reflecting the highly collaborative nature of the programme. Based within the Data-driven Biology Group, the postholder will develop and validate AI and data science tools for multi-cancer risk prediction models using population-scale, multimodal datasets, including electronic health records, administrative data, and multi-omic data.

About you

You will have a solid quantitative background and an interest in applying data-driven and AI methods to questions that matter for public health. We are looking for someone who can work confidently with large and varied health and omic datasets, and who enjoys developing and testing new analytical approaches. Experience in machine learning and combining different data types will be critical to the role, but we are just as interested in your ability to think clearly, learn new methods, and work well with others. CD3 is a highly collaborative programme, and the post calls for someone who is comfortable engaging with researchers from different disciplines and institutions.

As well as additional benefits that will make your life easier, such as a generous holiday allowance and additional university closure days. We will help you find a good work-life balance with flexible, or even part-time, working hours. We will support your long-term future too, with access to the Universities Superannuation Scheme (USS)*, subsidised health and fitness facilities and a range of discounts. 

This post is offered on a three-year. Part-time appointments (up to 80%) will be considered on a pro-rata basis.

For additional information or informal enquiries before submitting your application, please contact Prof. Owen Rackham (O.J.L.Rackham@soton.ac.uk)


United Kingdom, Durham

A part-time fixed-term Project Officer position is available to support a new research project within the Durham Quantum Light and Matter group. The position is funded by UKRI and the research project is focussing on understanding the behaviour of interacting many-body quantum systems. The project is a collaboration with researchers in Durham, London, Birmingham, France, Germany and the USA.The post holder will work directly with Prof. Simon Cornish (Physics) the science lead and overall programme manager. To find out more, visit the project webpage: Durham Quantum Light and Matter webpage:

Please note that this role may involve travel beyond the University, including visits to project partner institutions, external events and collaborative meetings. Flexibility and willingness to travel are therefore important aspects of the role.

This role is offered on a fixed term (5 years) part time (14 hours per week) basis.Working pattern will be subject to agreement.

The target start date for this position is no later than 1 February 2026.

What you are required to submit:


	A CV.
	A covering letteror statement which shows examples of how you meet all of the criteria within the Person Specification.


Contact details

If you would like to have a chat or ask any questions about the role, Professor Simon Cornish (s.) would be happy to speak to you.

The post is part time, and fixed term for a 5 year period.

When appointing to this role the University must ensure that it meets any applicable immigration requirements, including salary thresholds which are applicable to some visas.


Durham University

United Arab Emirates, Abu Dhabi

Description

The Prof. Sunil Kumar’s Research Group in the Division of Engineering, New York University Abu Dhabi, seeks to recruit a research assistant to develop AI-enabled healthcare applications.

Key Responsibilities:


	Develop and fine-tune computer-vision models, instance segmentation, and retrieval-based estimation from images and text metadata.
	Build and evaluate monocular depth pipelines and implement multimodal retrieval with re-rankers for robust profile selection.
	Design and train advanced AI models for digital twin: 3D model learning, prediction models from imaging and molecular data, model-based simulation coupling, and uncertainty-aware outputs for lab/clinical validation.
	Work with 3D datasets, time-series sensors, and multi-omics or assay data to create predictive models and digital twin prototypes.
	Maintain reproducible code, experiments, and model/ dataset versioning; develop deployment artifacts (Docker, CI/CD scripts) and support cloud/HPC model training.
	Plan, run and analyze pilot studies (SME pilots and lab validation); participate in data collection, annotation and lab assay coordination.
	Write up results and contribute to publications, technical reports and presentations for academic and non-academic stakeholders.


Minimum Qualifications:


	Bachelor’s or Master’s degree in computer science, electrical/computer engineering, applied mathematics, computational biology, bioengineering, or a closely related discipline.
	Solid experience training and evaluating AI models.
	Proficiency in Python and ML frameworks (PyTorch, TensorFlow).
	Experience with dataset curation, annotation workflows, FAISS/embedding retrieval, LLM-based parsing, RAG-style pipeline, and GPU/HPC training.
	Familiarity with 3D data processing or willingness to learn quickly.
	Publications, thesis work, or demonstrable projects in computer vision, multi-modal ML, digital twins or biomedical ML.
	Familiarity with uncertainty quantification and model explainability methods.
	Strong software engineering practices: Git, reproducible experiments, modular code, deploying models in cloud (AWS/GCP) and containerized services (Docker, Kubernetes).
	Good written and verbal communication skills and ability to work collaboratively across interdisciplinary teams.


For consideration, applicants need to submit a cover letter, curriculum vitae with full publication list statement of research interests, transcript and three letters of reference, all in PDF format. If you have any questions, please email Prof. Prabodh Panindre at prabodh@nyu.edu.

The terms of employment are very competitive and include housing and educational subsidies for children. Applications will be accepted immediately and candidates will be considered until the position is filled. Please visit our website at https://nyuad.nyu.edu/en/about/careers/postdoctoral-and-research.html for instructions and information on how to apply.

About NYU Abu Dhabi

https://nyuad.nyu.edu/en/

NYU Abu Dhabi is the first comprehensive liberal arts and research campus in the Middle East to be operated abroad by a major American research university. Times Higher Education ranks NYU among the top 30 universities in the world, making NYU Abu Dhabi the highest-ranked university in the UAE and MENA region. NYU Abu Dhabi has integrated a highly selective undergraduate curriculum across the disciplines with a world center for advanced research and scholarship. The university enables its students in the sciences, engineering, social sciences, humanities, and arts to succeed in an increasingly interdependent world and advance cooperation and progress on humanity’s shared challenges. NYU Abu Dhabi’s high-achieving students have come from over 120 countries and speak over 100 languages. Together, NYU's campuses in New York, Abu Dhabi, and Shanghai form the backbone of a unique global university, giving faculty and students opportunities to experience varied learning environments and immersion in other cultures at one or more of the numerous study-abroad sites NYU maintains on six continents.

NYUAD is committed to upholding a culture of non-discrimination, anti-harassment, dignity, and mutual respect; providing equal access and opportunity; and fostering academic excellence in learning, research, and teaching.

UAE Nationals are encouraged to apply.


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