Pepperdine University

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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

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, Glasgow

Closing date: 03/01/2025
Salary Range: £34,866
FTE: 1
Contract Type: Fixed Term (1 year)

The Research Assistant, alongside PhD and other PDRA workers assigned to the project will design and enable the synthesis of novel small molecule inhibitors of the Androgen Receptor. This will require a thorough grounding in synthetic organic chemistry, allied with experience of array synthesis approaches, as well as associated purification and analysis techniques. From consideration of biological data generated by programme team colleagues, the PDRA (with input from the PI) will lead on the design and synthesis of new compounds which meet agreed lead candidate criteria. Direct experience of academic or industrial medicinal chemistry is an advantage but not considered essential. The PDRA is expected also to engage in knowledge exchange processes with Aberdeen colleagues and other external partners as appropriate, as well as assisting in the administrative duties associated with the group of Prof Jamieson at the University of Strathclyde.

For informal enquires, please contact Professor of Medicinal Chemistry, Craig Jamieson (craig.jamieson@strath.ac.uk).

please click here for further details


University of Strathclyde

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, London

Student Registry - Student Records & Data Team

Location:  Avery Hill Campus
Salary:  £27,344 to £30,505 plus £5400 London weighting per annum
Contract Type: Fixed Term - until December 2025
Closing Date: Thursday 02 January 2025
Interview Date: To be confirmed
Reference:  4804

 

The Directorate of Student and Academic Services is seeking to appoint a Student Records Administrator.

 

Based within the Student Records team they will be responsible for undertaking a range of administrative duties associated with the maintenance of student records. Ensuring accurate and up to date records within the Student Record System, as well as other tasks such as creating Progression and Award Board cohorts and ensuring accurate data for statutory reporting. 

Working with the Student Records team, colleagues across Student and Academic Services and Faculties, the post holder will on occasion be required to deputise for the Student Records Team Leader in their absence. The successful candidate will have proven experience in a demanding office environment whilst continuing to maintain high levels of service delivery. This role requires strong administrative skills as well as excellent interpersonal and customer service skills.

The post holder will work collaboratively with colleagues across the University, liaising with academic departments and professional services staff, to ensure delivery of an excellent student experience. 

For an informal discussion about the post please contact Francesco Malgieri on francesco.malgieri@gre.ac.uk.  

Should you have any queries please contact the People Directorate Team on peopleoperationssas@gre.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 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.

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.


Pepperdine University

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