Hungkuang 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
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Aalto 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

Singapore

FACULTY POSITIONS (AT ALL LEVELS) IN COMPUTER SCIENCE, COMPUTER ENGINEEERING AND INFORMATION SECURITY 

The Singapore Institute of Technology (SIT) is Singapore’s first University of Applied Learning, offering industry-relevant degree programmes that prepare its graduates to be work- and future-ready professionals. Its mission is to maximise the potential of its learners and to innovate with industry, through an integrated applied learning and research approach, so as to contribute to the economy and society.

The university’s unique pedagogy integrates work and study, embracing authentic learning in a real-world environment through collaborations with key strategic partners. Its focus on applied research with business impact is aimed at helping industry innovate and grow. Targeted to be ready in 2024, SIT’s centralised campus within the larger Punggol Digital District will feature a vibrant learning environment where academia and industry will be tightly integrated with the community.

SIT espouses an applied learning approach and offers degrees with a strong focus on science and technology. Our faculty work closely with industry on translational research and innovation, as well as provide consultancy on solutions to industry challenges. This well-established nexus with industry endows our graduates with deep skills and work-ready training experience – attuning them to the needs and demands of the future economy.

SIT is also establishing strategic live test beds known as ‘Living Labs’ both within and beyond its upcoming Punggol campus to support greater experiential learning and strengthen its applied research offerings. The university’s pool of ICT experts works with multi-disciplinary teams to drive the horizontal tech enablers required to support SIT’s strategic translational research.

As a young university, we encourage innovation and seek the right candidates to join us in realising our vision. We offer competitive remuneration, generous employment benefits, access to funding to undertake research of relevance to industry, and opportunities to inspire and nurture the next generation of skilled and work-ready graduates. We currently have positions available at all levels, from Lecturer to Full Professor, in the following areas: 


	Information Security: Mobile/distributed systems security, Cyber Physical Systems security, security analytics, digital forensics, vulnerability assessment, malware analysis and defence, Privacy-enhancing technologies, AI security.  
	Computer Science and Software Engineering: SDLC, requirement analysis, design, testing, optimisation, analysis, simulation, database, computer graphics, distributed systems, computer vision, video analytics  
	Emerging Fields: IIoT, computational fintech, robot-human interaction, Trustworthy AI, Explainable AI, Large Language Models, Quantum Computing.  
	We have established research teams in operational cybersecurity, AR/VR/HCI and immersive technologies, future transportation solutions, AI, future communications/5G, BCI and embedded systems. We welcome candidates who can complement or strengthen these areas.


Successful candidates will join the Infocomm Technology (ICT) Cluster (one of five academic clusters in SIT) as members of a team of accomplished experts who are passionate about higher education and deeply involved in industry transformation through applied research programmes.   

Faculty in the ICT Cluster undertake funded industry-relevant research, teach courses in Computer Science, Computer Engineering, Information Security and Software Engineering, as well as supervise graduate industry masters and doctorate students in relevant topics. They are also provided with paid leave to undertake consultancy work with industry and/or spend time attached with industry. 

We will prioritise collegial and team-spirited candidates with an earned PhD in a related discipline from a reputable university, plus relevant work experience or experience of industry-linked applied research projects.

Applications will be accepted until the positions are filled. All applications must be submitted electronically via the "Apply Now" button below. 


Singapore Institute of Technology (SIT)

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.  



United Arab Emirates, Abu Dhabi

Description

The Public Health Research Center (PHRC) at New York University Abu Dhabi seeks to recruit a talented, motivated and experienced Research Engineer with expertise in creating, developing, testing and maintaining high quality applications and in particular Laboratory Information Management Systems (LIMS). The role of the selected applicant will focus on supporting the Center’s mission by developing a comprehensive system allowing the adequate and effective management of samples and all its associated data. The PHRC aims to understand the basis of health outcomes and traits related to the most common non-communicable diseases in the UAE by investigating and integrating when possible epidemiological, clinical and genetic data.

The appointed applicant will be in charge of creating, developing, configuring and maintaining a LIMS system customized to the needs of the PHRC research projects including but not limited to sample and associated data inventories, development for rapid, efficient and automated data tracking and retrieval workflows. The successful candidate will also contribute to write documentation for the developed tools, pipelines/workflows, SOPs and resources available. The candidate will have to integrate into the existing team of scientists and participate and lead training sessions of the PHRC team when needed. The candidate must have excellent organizational and communication skills with a high level of proficiency in English and the ability to work effectively in a team as well as individually.

 REQUIRED QUALIFICATIONS


	Master’s degree in Computer science, Information Systems or equivalent;
	A minimum of 2 years of related working experience in LIMS environment development, or related environment
	Experience with validation procedures within a software development environment (user acceptance testing, issue tracking/reporting/testing etc.).
	A minimum of 3 years in SDLC (software development life cycle).
	Experience in both Windows and Linux OS.
	A minimum of 3 years’ experience in relational databases (e.g. MySQL) and developing front-end database interfaces.
	A minimum of 3 years’ experience in at least one of the following languages Perl/Python/Java/PHP.
	Experience in server administration and maintenance.


For consideration, applicants need to submit, through the Interfolio platform, a cover letter, curriculum vitae, transcript, research statement and three letters of reference, all in PDF format. If you have any further questions, please send an email to Dr. Youssef Idaghdour, at yv8@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.

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.


Hungkuang University

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Impact Rankings

Impact Rankings 2024801-1000^th

No Poverty 2024401-600^th

Zero Hunger 2024401-600^th

Good Health and Wellbeing 2024201-300^th

Clean Water and Sanitation 2024601-800^th

Decent Work and Economic Growth 2024301-400^th

Responsible Consumption and Production 2024301-400^th

Climate Action 2024601-800^th

Partnership for the Goals 20241001-1500^th

Discover similar universities

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Hungkuang University

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Impact Rankings

.css-1lk1zhk{display:block;-webkit-box-flex:1;-webkit-flex-grow:1;-ms-flex-positive:1;flex-grow:1;}Impact Rankings 2024.css-4ju6x1{display:block;font-size:1.25rem;line-height:1.375;font-weight:600;color:#595959;}.css-4ju6x1>sup{font-size:65%;display:inline-block;width:0;word-wrap:normal;}801-1000th

No Poverty 2024401-600th

Zero Hunger 2024401-600th

Good Health and Wellbeing 2024201-300th

Clean Water and Sanitation 2024601-800th

Decent Work and Economic Growth 2024301-400th

Responsible Consumption and Production 2024301-400th

Climate Action 2024601-800th

Partnership for the Goals 20241001-1500th

Discover similar universities

Impact Rankings 2024801-1000^th

No Poverty 2024401-600^th

Zero Hunger 2024401-600^th

Good Health and Wellbeing 2024201-300^th

Clean Water and Sanitation 2024601-800^th

Decent Work and Economic Growth 2024301-400^th

Responsible Consumption and Production 2024301-400^th

Climate Action 2024601-800^th

Partnership for the Goals 20241001-1500^th