École Nationale Supérieure de Biotechnologie Taoufik Khaznadar (ENSB)

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Higher National School of Biotechnology Taoufi Khaznadar (ENSB)

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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.  



Singapore Institute of Technology (SIT)

United Kingdom, Newcastle upon Tyne

ABOUT THE ROLE

This is an exciting opportunity to contribute to a ground-breaking project focused on developing sustainable cooling systems, with an emphasis on advancing energy-efficient technologies for air conditioning. As a Senior Postdoctoral Research Fellow, you will play a central role in technology development, project execution, data collection, and analysis, while also providing critical guidance on system design to ensure innovative and practical solutions.

The project aims to address the challenge of improving cooling efficiency for all applications, prioritizing sustainability, and scalability. Your role will involve collaborating with academic and industry partners from both the UK and Pakistan, fostering impactful results and driving advancements in sustainable cooling technologies.

This position offers a unique chance to work at the intersection of cutting-edge research and real-world application, contributing to a high-impact initiative that bridges academia and industry while addressing global environmental challenges.

This role is fixed term for 36 months.

ABOUT THE TEAM

Find out more about Mechanical Engineering at Northumbria University: https://www.northumbria.ac.uk/about-us/academic-departments/mechanical-and-construction-engineering/research/

ABOUT YOU

Further information about the requirements of the role is available in the person specification.

Please contact project lead Dr. Muhammad Wakil Shahzad (muhammad.w.shahzad@northumbria.ac.uk) for additional information and an informal phone conversation.

To apply for this vacancy please click 'Apply Now'. Your application should include a covering letter and a CV.

ABOUT US

Northumbria University is a research-intensive university that unlocks potential for all.  We change lives regionally, nationally, and internationally through education and research, tackling the global challenges of our age to transform society and the economy. Find out why we were named Times Higher Education’s University of the Year in 2022 and Modern University of the Year in The Times and Sunday Times Good University Guide 2025.

Northumbria recorded the biggest rise of any UK university for research power in the Research Excellence Framework for the second time in 2021 and is now ranked top 25 in the UK for this measure.

One of the largest universities in the UK with over 37,000 students from more than 140 countries, filled with world-leading research, award-winning partnerships, and students at the heart of an outstanding experience. Discover more about us.

Northumbria University is a great place to work. We empower our exceptional people to achieve shared ambitions and promote a positive work life balance. We offer a wide range of benefits including excellent pension schemes, flexible working, a generous holiday entitlement, continued commitment to your learning and development and more.

Our Northumbria Values are guiding principles that define who we are, what we do and what is important to us. Our Values are: Academic Excellence; Innovation; Inclusivity; Collaboration; and Ambition.

Our Behaviours describe how we do things and how we work together at Northumbria, reflecting our culture and our decision-making. Our Behaviours are: We listen and learn, we support one another to success, we respect everyone and their contributions, we trust in ourselves and each other and we are bold.

Our Values and Behaviours were co-created by colleagues from a range of roles across the University, who worked collaboratively to consider what it feels like to work for Northumbria, and where we need to continue to transform together to achieve what’s important to us.

Please visit Our Values and Behaviours page to find out more.

We are an on-campus organisation where colleagues work regular patterns of hours and on campus, with some flexibility on the timing of their hours and the location of their work in discussion with their manager. Our campus locations include our City and Coach Lane Campuses in Newcastle upon Tyne and our London campus.

Northumbria University is committed to creating an inclusive culture where we take pride in, and value, the diversity of our staff. We encourage and welcome applications from all members of the community. The University holds bronze Athena Swan and Race Equality Charter awards in recognition of our commitment to advancing gender and race equality, we are a Disability Confident Leader and are participating in the Stonewall Diversity Champion Programme. We also hold the HR Excellence in Research award for implementing the concordat supporting the career Development of Researchers and are members of the Euraxess initiative to deliver information and support to professional researchers. The University has implemented a range of flexible working arrangements, and we are happy to explore candidate requirements as part of the recruitment process.

We are committed to keeping your data safe so it's important for you to know how we use any personal data you give us. For more detailed information, access our Privacy Policy.


Northumbria University, Newcastle

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

China, Ningbo

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.

The University of Nottingham Ningbo, China, a pioneer in Sino-foreign tertiary education, is rapidly expanding.  It is looking for ambitious, talented academics with a passion for teaching as well as research flair to join its team of science and engineering experts. UNNC is part of the University of Nottingham’s Global University, and offers unique teaching and research opportunities in a highly dynamic economy.

The successful candidate will be expected to contribute to teaching and curriculum development for undergraduate and postgraduate programmes in Chemical and Environmental Engineering. An important part of the role will be to teach students in Chemical and Environmental Engineering degree. Candidates should be qualified to deliver courses in the core curriculum of a Chemical and Environmental Engineering programme.

The person appointed will also be expected to conduct ongoing original research for publication and play a lead role in collaborative research projects The purpose of this role will be to lead and deliver individual and collaborative research and teaching in the area of Chemical and Environmental Engineering, and make a contribution to the direction of research programmes in the Department/School of Chemical and Environmental Engineering.

Candidates must have a PhD degree in Chemical Engineering or a closely related discipline, and excellent communication and presentation skills in English. Knowledge and experience of industrial design and process safety are desirable. Experience of supervising student research up to the PhD level, and experience of teaching, tutorial or laboratory work at undergraduate and/or postgraduate levels in an English speaking institution are essential.

Salary will be within the range of RMB 439,794 to RMB 579,126 per annum, depending on skills and experience (salary progression beyond this scale is subject to performance). In addition, an attractive package including employment support allowance, schooling and insurance will be provided for international appointments.

The post will initially be offered on a fixed term contract with the University of Nottingham, Ningbo, China for a period of five years starting October 2024 or as soon as thereafter. This contract may be extended on an indefinite basis by mutual agreement.

Informal enquiries may be addressed to: Professor Philip Hall, Head of Department of Chemical & Environmental Engineering – The University of Nottingham Ningbo China, email: Philip.Hall@nottingham.edu.cn Please note that applications sent directly to this email address will not be accepted.

Interviews will take place in Ningbo, China, if feasible – virtual interviews may also held. Please be advised that normally your references will be contacted prior to the interview.

For more details and/or to apply on-line please access: 

https://jobs.nottingham.edu.cn/job/184021/

If you are unable to apply on-line please contact the Human Resources Department, Tel: 86 574 8818 000 (Ext. 8404), Email: Job@nottingham.edu.cn.  


University of Nottingham Ningbo, China

United Arab Emirates, Abu Dhabi

Postdoctoral Associate/Research Scientist in the Division of Engineering (Civil and Urban Engineering) - Dr. Mohamed Moustafa 

Description

The Future-Generation of Resilient and Infrastructure Design Technology Hub (Future-GRID TecH) in the Division of Engineering at New York University Abu Dhabi, seeks to recruit one or more motivated post-doctoral associates (or research scientist for experienced candidates with 5 years of post-PhD experience). The candidates will work under the supervision of Future-GRID TecH director Dr. Mohamed Moustafa to carry out cutting-edge research in the broad area of future structures and resilient infrastructure systems with interest in applications of new and emerging technologies. Particular areas of interest include:


	advanced construction and reinforcement materials (UHPC, ECC, SMA)
	UHPC mix development, material characterization, modeling, and structural design
	structural 3D printing (metals, concrete, and composites)
	computational mechanics and structural topology optimization
	vision-based structural health monitoring
	autonomous and drone-based infrastructure inspection and vibration monitoring


Successful candidates must hold a PhD degree in Civil, Structural, Mechanical, or Material Engineering. Other related field such as Computer Science, Nuclear Engineering, and Material Science are also welcomed. Required qualifications include: strong communication and presentation skills; a track record in writing and publishing peer-reviewed journal publications; and previous or relevant experience in mentoring or supervising undergraduate student research or junior graduate students.

A formal training, education, or certification in a secondary area (beyond the main PhD focus) such as additive manufacturing, advanced/hybrid manufacturing, machine learning, artificial intelligence, computer vision, robotics, UAVs, computational fluid dynamics, etc. is a plus. Other preferred qualifications include: expertise in programming and coding (preferably using Python and C ) and GUI development; expertise in computational mechanics and finite element simulation and modeling; expertise in laboratory and multi-scale experimental testing at the material, component, and structural levels.  

The candidates will work in a multidisciplinary environment consisting of PhD-level scientists and undergraduate students, conduct high-quality “innovative and independent” experimental, analytical, and/or computational research, publish research work and results in scientific peer-reviewed journals and conferences, mentor undergraduate students, and participate in writing research grant proposals.

To be considered, all applicants must submit the following documents in PDF format via Interfolio:


	cover letter
	curriculum vitae with full publication list
	statement of research interests and plan
	three sample (recent and/or most relevant) journal publications
	contact details of two references


The terms of employment include a highly competitive salary, medical insurance, housing allowance, annual home-leave travel, and educational subsidies for children (if applicable). Applications will be accepted immediately and candidates will be considered until the positions are filled.

If you have any questions or require more information, please email: mohamed.moustafa@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

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Good Health and Wellbeing 20241001+

Quality Education 20241501+

Partnership for the Goals 20241501+

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École Nationale Supérieure de Biotechnologie Taoufik Khaznadar (ENSB)

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No Poverty 20241001+

Good Health and Wellbeing 20241001+

Quality Education 20241501+

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