Gautam Buddha University

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Hong Kong

THE HONG KONG POLYTECHNIC UNIVERSITY  

With over 85 years of rich heritage, The Hong Kong Polytechnic University (PolyU) has evolved alongside society and made pivotal contributions to the development of Hong Kong, the Nation and the world.  The University pursues world-class excellence in education, research and knowledge transfer to nurture socially responsible leaders and professionals, as well as to drive impactful research and innovation.  PolyU will strive to continually excel as an innovative world-class university that makes a positive impact on society, living up to the University’s motto: “To learn and to apply, for the benefit of mankind”.

Ranked among the top 100 universities globally by well-known ranking organisations such as Quacquarelli Symonds (QS), Times Higher Education (THE) and U.S. News & World Report, PolyU offers a wide range of world-class educational and research programmes in seven faculties (including the Faculty of Computer and Mathematical Sciences to be established on 1 January 2025) and three independent schools.  PolyU has furthermore achieved remarkable results in the latest QS World University Rankings by Subject 2024 – it is ranked in the global top 20 for five subjects, is first in Hong Kong for four subjects, and is in the global top 100 for 21 subjects.

DEPARTMENT OF APPLIED MATHEMATICS

Assistant Professor in Applied Optimization and Operations Research / Data Science and Analytics / Applied Statistics and Financial Mathematics / Engineering and Computational Mathematics / Mathematical Science (Ref. 241220013)

The Department of Applied Mathematics (AMA) will be a part of the newly formed Faculty of Computer and Mathematical Sciences, which will be established on 1 January 2025.  The Department offers Bachelor of Science (Honours) Scheme in Data Science, and makes a significant contribution to most of other academic programmes of the University by providing service teaching.  It also offers master programmes in Applied Mathematics for Science and Technology with specialisms in Actuarial and Investment Science, Operational Research and Risk Analysis, Data Science and Analytics, and Quantitative Finance and FinTech.  Members of the Department have expertise in applied optimization and optimal control, engineering computation, operational research, management science and applied statistics, FinTech, data science and machine learning.  There are currently 49 academic staff and about 159 research personnel in the Department.  Please visit the website at http://www.polyu.edu.hk/ama for more information about the Department.

The Department has established a Joint Laboratory of Applied Mathematics with the Academy of Mathematics and Systems Science of the Chinese Academy of Sciences.  The appointee is expected to be actively involved in the activities of the Laboratory.

Duties

The appointee will be required to:

(a)   teach and contribute to curriculum development at undergraduate and postgraduate levels;  

(b)   supervise MPhil and PhD students;  

(c)   engage in scholarly research, consultancy and other scholarly activities leading to publications in top-tier refereed journals and award of research grants;  

(d)   undertake academic and departmental administrative duties; and  

(e)   perform any other duties as assigned by the Head of the Department or his delegates.  

Qualifications

Applicants should:

(a)   have a PhD in Mathematics / Statistics / Financial Mathematics / Operations Research / Computational Mathematics / Applied Mathematics or a closely related field;  

(b)   have expertise in applied statistics, operation research or mathematics;  

(c)   have an established track record in research and scholarship, including refereed publications and external grant applications;  

(d)   have a demonstrated commitment to excellence in teaching; and  

(e)   be highly proficient in written and spoken English.  

Conditions of Service

A highly competitive remuneration package will be offered.  Appointment will only be on a fixed-term gratuity-bearing contract. 

Application

Please submit an application through PolyU’s career website (https://jobs.polyu.edu.hk/academic).  Consideration of applications will commence on 10 January 2025 until the position is filled.  The University’s Personal Information Collection Statement for recruitment can be found at https://www.polyu.edu.hk/hro/careers/pics_for_recruitment/.

PolyU is an equal opportunity employer, dedicated to fostering an environment that embraces diversity and demonstrates inclusion of people from all backgrounds, cultures, identities and experiences where all members of the University are treated with fairness, dignity and respect. To learn more about the University’s “Statement on Equal Opportunities, Diversity, and Inclusion”, please visit our website at https://www.polyu.edu.hk/hro/equal_opportunities_diversity_and_inclusion/


The Hong Kong Polytechnic University

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

Australia, Clayton

Job No.: 670005

Location: Clayton campus

Employment Type: Full-time

Duration: Continuing appointment

Remuneration: $114,951 - $136,505 pa Level B / $140,812 - $162,366 pa Level C (plus 17% employer superannuation)


	Amplify your impact at a world top 50 University
	Join our inclusive, collaborative community
	Be surrounded by extraordinary ideas - and the people who discover them


The Department of Econometrics and Business Statistics at the Monash Business School integrates three areas of research focus and education: Actuarial Studies, Business Analytics, and Econometrics, and boasts well-established programs with strong national and international reputation in all fields. The department plays an active role in the open-source software movement, including contributions to the R Foundation. Our extensive engagement with industry ensures that we maintain a cutting-edge, practical focus that prepares our students for dynamic careers. 

The Opportunity

Join the pinnacle of academic excellence at Monash Business School and help propel your career in academia. The Department of Econometrics & Business Statistics at Monash University is a global powerhouse with a dynamic team of approximately 50 leading academics and a similar number of PhD students, all with strengths in Actuarial Science, Business Analytics and Econometrics.

The Role

The department seeks a dynamic Lecturer or Senior Lecturer (Education-focused) to join our collaborative team. The role involves significant contributions to teaching, educational leadership, and innovative practices, fostering world-class learning experiences. The candidate will stay current in their discipline and further develop their scholarly and professional expertise.

Key Responsibilities:


	Develop a range of resources, learning materials, practice tasks, authentic assessments
	Deliver lectures, workshops, and seminars
	Design, implement and review educational innovations
	Coordinate a major or field of study or award program


About You

For the Level B Education Focused Lecturer Role:


	Qualifications: A doctoral qualification in econometrics, statistics, data science, machine learning, or a closely related area
	Education Prowess: Teaching experience across multiple units, including in large classes, in a tertiary environment
	People Skills: Possess a high level of interpersonal skills, motivating and actively engaging with students at a tertiary level


For the Level C Education Focused Senior Lecturer Role:


	Qualifications: A doctoral qualification in econometrics, statistics, data science, machine learning, or a closely related area
	Innovator: Demonstrated leadership in education, including teaching excellence and pedagogical innovation, demonstrated by student evaluations, innovative presentation and curriculum development, etc.
	People Skills: Possess a high level of interpersonal skills, motivating and actively engaging with students at a tertiary level


About Monash University

At Monash, work feels different. There’s a sense of belonging, from contributing to something groundbreaking – a place where great things happen.

We value difference and diversity, and welcome and celebrate everyone's contributions, lived experience and expertise. That’s why we champion an inclusive and respectful workplace culture where everyone is supported to succeed.

Together with our commitment to academic freedom, you will have access to quality research facilities, infrastructure, world-class teaching spaces, and international collaboration opportunities. 

Be part of our story. Work with us to #ChangeIt.

Monash supports flexible and hybrid working arrangements. We have a range of policies in place enabling staff to combine work and personal commitments. This includes supporting parents.

To Apply

Your application must address the Key Selection Criteria. For further instructions on how to apply, please refer to 'How to apply for Monash Jobs'. 

We encourage applications from Aboriginal and Torres Strait Islander people, culturally and linguistically diverse people, people with disabilities, neurodivergent people, and people of all genders, sexualities, and age groups.

We are committed to fostering an inclusive and accessible recruitment process at Monash. If you need any reasonable adjustments, please contact us at hr-recruitment@monash.edu in an email titled 'Reasonable Adjustments Request' for a confidential discussion.

Your employment is contingent upon the satisfactory completion of all pre-employment and/or background checks required for the role, as determined by the University.

Enquiries:  Professor George Athanasopoulos, Head of the Department of Econometrics and Business Statistics, Econometrics & Business Statistics, BusEco-EBS.HOD@monash.edu 

Position Description:

Level B - Lecturer (Education focused) – Econometrics and Business Statistics

Level C - Senior Lecturer (Education focused) – Econometrics and Business Statistics

Applications Close: Sunday 19 January 2025, 11:55pm AEDT


Monash University

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

United Kingdom, London

FEHHS Human Sciences: Public Health

Location: Greenwich Campus
Salary: £37,999 to £43,878 plus £4170 London weighting per annum
Contract Type: Permanent
Closing Date: Sunday 19 January 2025
Interview Date: To be confirmed
Reference: 4816

Lecturer in Public Health with knowledge of public health as applied to mental health and wellbeing.

As a result of strong student recruitment we are seeking an additional staff member to join our growing public health team in the School of Human Sciences. Ideally, we are looking for a candidate with knowledge of knowledge of public health as applied to mental health and wellbeing.

You will be joining a School and Faculty that is building a strong interdisciplinary and cross-professional approach to solving the grand challenges facing society. We are looking for colleagues who will have a commitment to maintaining and building the University’s excellence in teaching and learning, and who are doing research that has the potential for significant long-term academic and societal impact.

As a faculty we also welcome candidates whose research work will resonate with one or more new interdisciplinary Faculty Research Centres within the Institute for Lifecourse Development.

The school has an active and growing research base. We had a strong performance in REF2021 particularly with regard to ‘research environment’. The University is currently rated TEF GOLD, reflecting our excellent teaching and learning. The school was nominated as ‘School of the Year’ in the Student Led Teaching awards, 2023.

We are looking to recruit an individual with a developing track record of scholarly outputs and professional activities who, at the same time, is able to demonstrate commitment to teaching excellence and innovation as well as appropriate experience of teaching in the HE sector for this level.

Informal enquiries can be made to Dr Charlotte Jeavons (Head of School); email: c.jeavons@gre.ac.uk

Should you have any queries please contact the People Directorate Team on peopleoperationsfehhs@greenwich.ac.uk

We operate a hybrid working policy, as set out in the University’s Working Principles and Guidelines.

Further details of the fantastic benefits and what we offer can be found here: Our benefits - what we offer | Jobs and careers | University of Greenwich

To apply, please visit the University of Greenwich vacancies page and complete all details, including the supporting statements (please note attached CVs and personal statements will not be seen by the recruitment panel at the application stage). Current Vacancies - Jobs at Greenwich

Employment Visa: Under the UK Government Points Based System scheme this role does meet the criteria to be sponsored for a Skilled Worker Route application.

We are looking for people who can help us achieve our Strategic Plan, through the values we expect for our whole university community, of being Inclusive, Collaborative and Impactful.

Academic Career Pathways

The university welcomes people from diverse and underrepresented communities who can help the university to achieve its mission.

We do this through taking positive action such as encouraging applications from Black, Asian and Minority Ethnic, disabled and LGBT+ people. As part of our commitment to Equality, Diversity and Inclusion, Time to Change Employer Pledge/Mentally Healthy Universities, we are committed to promoting and supporting the physical and mental health of all our staff, and removing barriers to improve inclusion.

We encourage applicants to disclose experience of mental health problems so we can support them fully during our recruitment process and make any necessary reasonable adjustments. Any information disclosed will be kept confidential and separate from the job application form.

We are making significant strides to understand and continuously improve our employees’ experience and we are committed to implementing progressive diversity talent management.


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