SASTRA University

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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

Ireland, Maynooth

Department: School of Business
Vacancy ID: 032841
Closing Date: 12-Jan-2025

We are seeking a highly motivated and skilled candidate to join our team as a Research Assistant, providing essential research and support to our dynamic and productive academic department. This role will involve significant contributions to the research teams working on the EU Horizon RIA project FLOW, focusing on the seamless development of user interface (UI) and user experience (UX) for an innovative EV mobile application in the renewable energy sector. The Research Assistant will play a key role in supporting the UI/UX development process, including contributing to the design and optimization of user-friendly features tailored to EV application users, assisting with iterative improvements to enhance functionality and performance, identifying and resolving bugs in the application, and aiding in the preparation of technical reports and documentation.

Research Assistant Level 1 (2024) Salary Scale: €31,962 p.a. (1 point)

Appointments will be made in accordance with public sector pay provisions.

Closing Date: 

23:30hrs (local Irish time) on Sunday, 12th January 2025

Applications must be submitted by the closing date and time specified above. Any applications which are still in progress at the closing time on the specified closing date will be cancelled automatically by the system.

Late applications will not be accepted.

Maynooth University is an equal opportunities employer

The position is subject to the Statutes of the University


Maynooth University

United Kingdom, London

Digital Programme Management Office

Location: Greenwich Campus
Salary: £56,921 to £65,814 plus £5400 London weighting per annum
Contract Type: Permanent
Closing Date: Sunday 12 January 2025
Interview Date: To be confirmed
Reference: 4810

Our Information and Library Services Directorate delivers award winning IT services and support, library, academic and digital skills and learning enhancement to staff and students across the university. Our digital mission is to ensure everyone in our community is equipped to effectively use digital services, data and technology with confidence, efficiency and creativity in their learning, teaching, research and organisational support.

To support the “This is Our Time” university strategy and our digital sub-strategy, we are seeking to appoint a dynamic and experienced Senior Project Manager to the Digital Programme Management Office to help deliver projects with an IT focus support.

The successful candidate will be responsible for managing a varied portfolio of projects supporting the delivery of the Digital Strategy as well as championing the cause of project management and providing a ‘centre of excellence service’. This is an exciting time to join the University as we continue to support the University of its 2030 Strategy.

Applicants should possess demonstrable experience of managing a range of complex projects including both infrastructure and development projects and those with Business Change, have exceptional written and verbal communication skills and possess relevant professional certification.

To find out more about our team, visit our Digital Recruitment webpage.

For an informal discussion about the post please contact Rayna Lloyd on ils-admin@greenwich.ac.uk

Should you have any queries please contact the People Directorate Team on peopleoperationsils@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

You don’t meet all the requirements?
Studies show that women and Black, Asian and minority ethnic people are less likely to apply for a job unless they meet every criteria. So if you’re excited about this role but your experience doesn’t align perfectly with the job description, we’d love you to still apply. You might just be the person we’re looking for.

Employment Visa: Under the UK Government Points Based System scheme this role does/does not 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.

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.


University of Greenwich

Hong Kong, Tuen Mun

Lingnan University is one of the eight publicly funded institutions in the Hong Kong Special Administrative Region (HKSAR) and has the longest established tradition among the local institutions of higher education. It is widely recognised for providing quality education with a focus on whole-person development and conducting high-impact research for a better world. Moving forward, Lingnan University is well positioned to take lead as a comprehensive university in arts and sciences in the digital era, with impactful research and innovations.

Lingnan University offers undergraduate, taught postgraduate, and research postgraduate programmes in the Faculties of Arts, Business, Social Sciences, and the Schools of Data Science, Graduate Studies and Interdisciplinary Studies. To foster interdisciplinary collaboration and scientific progress, Lingnan University established the Lingnan University Institute for Advanced Study (LUIAS), attracting distinguished scholars from around the world to collaborate with its faculty and students. With traditional strengths in arts, business, social sciences, and interdisciplinary studies, the University aims to equip students with practical knowledge and critical thinking skills to thrive in the future. Subsequent to the establishment of the School of Data Science and LUIAS, Lingnan University is transforming into a hub for global leaders to develop and promote human-centric technology and social policies. Further information about Lingnan University is available at https://www.ln.edu.hk/.

Applications are now invited for the following posts:

Assistant Professor of Teaching
Department of Accountancy
(Post Ref.: 24/380)

The Department has vacancies for the posts of Assistant Professor of Teaching. The appointees are expected to contribute to high quality teaching.

General Requirements

Applicants should have a PhD degree in Accountancy or a related discipline and must demonstrate excellent teaching record. The appointees are expected to teach a variety of subjects including law in business and other accounting functional courses, such as managerial and financial accounting. The successful candidates should maintain the Association to Advance Collegiate Schools of Business (AACSB) qualification through producing peer reviewed journal publications or other intellectual contributions, engaging in professional development activities, responsible for curriculum development, and student advising and mentoring. The appointees are also expected to help the Department to maintain good relationship with professional bodies and business, reach out business by knowledge transfer, as well as to liaison with professional bodies to obtain (re)accreditation status of our accounting program(s).

Appointment

The conditions of appointments will be competitive. The remuneration will be commensurate with qualifications and experience. Fringe benefits include annual leave, medical and dental benefits, mandatory provident fund, gratuity and incoming passage and baggage allowance for the eligible appointees. Appointments will normally be made on a fixed-term contract of up to three years.

Application Procedure (online application only)

Please click "Apply Now" to submit your application. Applicants shall provide names and contact information of at least three referees to whom applicants’ consent has been given for their providing references. Personal data collected will be used for recruitment purposes only.

We are an equal opportunities employer. Review of applications will continue until the posts are filled. Qualified candidates are advised to submit their applications early for consideration.

The University reserves the right not to make an appointment for the posts advertised, or to fill the posts by invitation or by search. We regret that only shortlisted candidates will be notified.


Lingnan University

United Kingdom, Egham

School of Performing and Digital Arts (Foundation Year)

Location
Egham

Salary
£48,619 to £57,429 per annum - including London Allowance

Post Type
Full Time

Closing Date
23.59 hours GMT on Tuesday 21 January 2025

Reference
1024-328-R

Right to work: Applications from job seekers who require sponsorship to work in the UK are welcome and will be considered alongside all other applications. For further information visit the UK Visas and Immigration website.

Full-time, Permanent

Applications are invited for the post of Teaching-Focused Lecturer in Computer Science on Integrated Foundation Year (IFY) Programmes at Royal Holloway, University of London.

The well-established and successful IFY at Royal Holloway teaches and supports over 400 students per year across a broad range of disciplines. We are currently expanding the staffing of our STEM (Science Technology Engineering and Mathematics) strand to enhance the foundation year experience for our students through more discipline-focused courses.

The successful applicant will be an experienced and talented teacher at Level 3, with a strong background in Computer Science, and a particular interest in programming. You will be experienced in using and teaching Python, Javascript, HTML, and CSS in a way that encourages and inspires students to embrace computer programming as part of their learning journey. You will also be an excellent communicator and versatile teacher, able to adapt your teaching methods to fit the diverse backgrounds of our students, in an approach centered on inclusivity, equity and the provision of skills for choice and opportunity.

In return, we offer a highly competitive rewards and benefits package including:


	Generous annual leave entitlement
	Training and Development opportunities
	Pension Scheme with generous employer contribution
	Various schemes including Cycle to Work, Season Ticket Loans and help with the cost of eyesight testing.
	Free parking


The post is based in Egham, Surrey where Royal Holloway is situated in a beautiful, leafy campus near to Windsor Great Park and within commuting distance from London.

For an informal discussion about the post, please contact Dr Deborah Harvey: d.harvey@rhul.ac.uk

For queries on the application process the Human Resources Department can be contacted by email at: recruitment@rhul.ac.uk

If you have previously applied for this position within the last three months, we kindly request that you do not reapply.

Please quote the reference: 1024-328-R

Closing Date: 23:59, 21 January 2025

Interview Date: To Be Confirmed

Further details: Job Description & Person Specification


SASTRA University

Rankings

World University Rankings 20241201-1500^th

Computer Science 2024801-1000^th

Engineering 2024801-1000^th

Life Sciences 2024601-800^th

Discover similar universities

Key Student Statistics

Subjects Taught at SASTRA University

Life Sciences601–800^th

Computer Science801–1000^th

Engineering801–1000^th

Company

Legal

SASTRA University

Rankings

Computer Science 2024801-1000th

Engineering 2024801-1000th

Life Sciences 2024601-800th

Discover similar universities

Key Student Statistics

Subjects Taught at SASTRA University

Life Sciences.css-umjwst{margin-left:0.5rem;vertical-align:middle;font-size:0.75rem;color:#595959;}601–800th

Computer Science801–1000th

Engineering801–1000th

Computer Science 2024801-1000^th

Engineering 2024801-1000^th

Life Sciences 2024601-800^th

Life Sciences601–800^th

Computer Science801–1000^th

Engineering801–1000^th