American University: Kogod

About Us The School of Biomedical Engineering & Imaging Sciences at King's College London is a world-leading center for research and innovation in medical imaging, image analysis, and biomedical engineering. Our interdisciplinary research brings together engineers, computer scientists, physicists, and clinicians to develop cutting-edge technologies that transform healthcare. This position is part of a prestigious Marie Skłodowska-Curie Actions (MSCA) Doctoral Network, offering exceptional training and networking opportunities across leading European research institutions. The MSCA programme supports the career development of early-stage researchers through international collaboration, specialized training, and exposure to both academic and industrial partners.  About The Role We are seeking an exceptional early-stage researcher to join our MSCA Doctoral Network as DC5 (Doctoral Candidate 5), focusing on quantitative phenotyping via generative modelling of quantitative MRI data. This exciting PhD position combines advanced machine learning with medical imaging physics to develop next-generation tools for biomarker extraction and clinical decision support. You will develop innovative generative models using vector quantised variational autoencoders (VQ-VAE) and transformer architectures to synthesise realistic quantitative MRI (qMRI) data with controlled anatomic variability. Your work will address a critical challenge in medical imaging: the limited availability of qMRI datasets. By augmenting models with phenotypes from non-quantitative MRI and disentangling image content from acquisition physics, you will create powerful tools that work across different imaging protocols. A key aspect of your research will be developing physics-aware models that bidirectionally map between non-quantitative and quantitative MRI data. Using Bloch equation simulations and cycle-consistent learning, you will create physics-invariant networks for biomarker extraction, segmentation, and classification. This work has significant potential to improve the robustness and generalizability of AI tools in clinical settings. The position offers unique international experience through a series of planned secondments at leading institutions, such as Amsterdam UMC (Netherlands) to apply your generative models to parameter mapping networks, University of Antwerp (Belgium) to validate your MRI simulator with preclinical data, and Institut Curie (France) to develop physics-invariant segmentation tools, to be discussed with the applicant You will receive comprehensive training in Advanced Machine Learning for medical applications, Scientific Computing, Image Processing, and Image Acquisition, while working alongside world-class researchers in medical imaging and AI. Expected milestones include: (1) a covariate-conditioned generative model of qMRI data (M18), (2) a fast physics-based MRI simulator (M24), (3) a bidirectional non-quantitative to qMRI mapping model (M30), and (4) an integrated joint generative framework (M42). This position is funded through a Marie Skłodowska-Curie Actions (MSCA) Doctoral Network grant and includes full enrollment in a doctoral programme with structured supervision and research training. The attractive salary package follows MSCA regulations, including living allowance, mobility allowance, and family allowance where applicable. This is a full-time post (35 hours/week), and you will be offered a fixed-term contract for 3 years / until the end of the PhD. About You To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria Hold a Master's degree or equivalent in computer science, biomedical engineering, medical imaging, mathematics, or related discipline Strong background in machine learning and deep learning, particularly in generative models (VAEs, GANs, transformers) Programming experience in Python and deep learning frameworks (PyTorch) Knowledge of medical image processing and analysis techniques Ability to understand and implement mathematical models, including physics-based models Excellent written and oral communication skills in English Ability to work independently and collaboratively within an international research network Meet MSCA mobility rule: at time of recruitment, must not have resided or carried out main activity in the UK for more than 12 months in the 3 years immediately prior to appointment Desirable criteria Experience with quantitative MRI (qMRI) techniques and physics Experience with vector quantised variational autoencoders (VQ-VAE) or similar models Knowledge of MRI physics and Bloch equation simulations Experience with medical image segmentation or classification tasks Publications in machine learning, medical imaging, or related fields Downloading a copy of our Job Description Full details of the role and the skills, knowledge and experience required can be found in the Job Description document, provided at the bottom of the page. This document will provide information of what criteria will be assessed at each stage of the recruitment process. Further Information  We pride ourselves on being inclusive and welcoming. We embrace diversity and want everyone to feel that they belong and are connected to others in our community. We are committed to working with our staff and unions on these and other issues, to continue to support our people and to develop a diverse and inclusive culture at King's. As part of this commitment to equality, diversity and inclusion and through this appointment process, it is our aim to develop candidate pools that include applicants from all backgrounds and communities. We ask all candidates to submit a copy of their CV, and a supporting statement, detailing how they meet the essential criteria listed in the person specification section of the job description. If we receive a strong field of candidates, we may use the desirable criteria to choose our final shortlist, so please include your evidence against these where possible. To find out how our managers will review your application, please take a look at our ‘How we Recruit’ pages. Grade and Salary: Marie Skłodowska-Curie Actions (MSCA) Doctoral Network programme salary package following MSCA regulations, including living allowance, mobility allowance, and family allowance where applicable Job ID: 133125 Close Date: 04-Jan-2026 Contact Person: Laura Zappulla Contact Details: laura.zappulla@kcl.ac.uk

Department: Psychology Vacancy ID: 039003 Closing Date: 06-Jan-2026 The Role  Maynooth University is committed to a strategy in which the primary University goals of excellent research and scholarship and outstanding education are interlinked and equally valued. We are seeking to recruit a Postdoctoral Researcher as part of a project entitled “PROMISE: Improving Mental Health Supports for People with Multiple Sclerosis in Ireland”. This project, a partnership between academics, clinicians and knowledge users, with significant integrated public and patient involvement (PPI), aims to identify the characteristics of effective mental health supports for people with multiple sclerosis (PwMS) and the strategies that can be implemented to improve the delivery of mental health services and supports for PwMS in Ireland. The PROMISE project is led by Principal Investigator (PI) Dr Rebecca Maguire in the Department of Psychology and the Assisting Living and Learning Institute, Maynooth University. This project is funded by the Health Research Board with co-funding from Multiple Sclerosis (MS) Ireland. The appointed researcher will be responsible for conducting many of the research and dissemination activities in the project under the supervision of the PI, with input from a wider project management group and a PPI steering committee. The successful candidate will have a PhD in Psychology, Social Science, Health or a related discipline, with experience in a range of different methodological approaches, including quantitative and qualitative research methods. Experience embedding public and patient involvement (PPI) in research, familiarity with multiple sclerosis or related conditions, and/or experience with mental health research and service provision in Ireland would be an advantage. Excellent organisational, academic writing and presentation skills are essential, as well as the ability to work both independently and collaboratively to meet project milestones. The researcher will be based in the Assisting Living and Learning Institute and the Department of Psychology at Maynooth University where they will join a supportive community of interdisciplinary researchers. Salary  Post-doctoral researcher: €46,305 – €46,905 p.a (with increment after 12 months) Appointments will be made in accordance with public sector pay provisions. Closing Date: 23:30hrs (local Irish time) on Tuesday the 6th of January 2026. Please note all applications must be made via our Online Recruitment Portal at the following link: https://www.maynoothuniversity.ie/human-resources/vacancies 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

A unique opening has arisen to become part of the Campus Safety Team here at the University of Surrey, supporting our students, staff members and visitors.  This is a great opportunity for an enthusiastic member to join our crucial campus service. You will be the ‘face’ of the University, dealing with everything from a student locked out of their room to crisis & emergency management, ensuring the campus is a safe environment for everyone, offering support and advice. Working hours for this role are pre-assigned “4 on, 4 off” shift patterns to support our 24/7 service. You will be expected to work 2 days then 2 nights for each “4 on” cycle. Role & Responsibilities:  Reporting into your Campus Manager, you’ll be overseeing the safety, security and welfare of those working, studying and visiting the University.  You’ll deal with both staff and students on a day-to-day basis, so we welcome application from those who have a keen interest in creating a warm and welcoming environment for our students and understands that every shift will come with new challenges to deal with. The role is varied by nature and a level of discretion will be needed to ensure that we are always doing what is best for our community.  As a member of Campus Safety Team, you will receive a comprehensive training plan to ensure that you are well equipped to deal with handling the common student and staff enquiries. The University of Surrey is amongst the highest achieving universities in the United Kingdom, named as University of the Year for Employment 2021. Surrey is one of only a few institutions to significantly rise in the NSS tables following an unprecedented 18 months for the sector. We are proud of our achievements, and you will be joining us at the start of an exciting journey to further position Surrey as a leading institution for Student Experience.  An enhanced DBS check is required for this position (at offer stage). What’s in it for you?:  We think Surrey is an amazing place to work, and we are carefully crafting a dynamic, flexible, and fun place to work and thrive. Alongside our gorgeous campus setting, collegiate on-site atmosphere and plentiful development opportunities, we also offer: Market leading Pension 32 Days Holiday  Salary Sacrifice benefits including subsidised rail fare, cycle to work scheme and on-site childcare Student discount eligibility Access to world-class facilities at discounted rates On-site parking for commuters, cafes, restaurants and coffee shops The University of Surrey is committed to providing an inclusive environment that offers equal opportunities for all. We place great value on diversity and are seeking to increase the diversity within our community. Therefore, we particularly encourage applications from under-represented groups, such as people from Black, Asian and minority ethnic groups and people with disabilities. Further details Job Description