Karelia University of Applied Sciences

Job Description 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. We are seeking a highly motivated and talented Research Fellow to join an exciting applied research project within the Infocomm Technology cluster at SIT. This project addresses the critical challenge of delivering real-time Artificial Intelligence (AI) services in Internet of Things (IoT) networks, where latency and timeliness are paramount. The successful candidate will be responsible for the end-to-end investigation of novel edge-assisted offloading strategies for IoT networks. The role will bridge rigorous theoretical work with hands-on offloading algorithm design and development for IoT networks. The core responsibility is to build and validate edge-assisted offloading strategies, complete with software APIs, through rigorous simulations and live demonstrations. This position is ideal for a researcher with a passion for solving complex problems at the intersection of wireless communications, edge computing, and machine learning, and who is eager to translate theoretical insights into practical, IoT systems. Key Responsibilities Participate in and manage the research project with Principal Investigator (PI) to ensure all project deliverables are met. Derivation of closed-form theoretical latency and timeliness expressions for cloud-hosted AI services and edge-assisted offloading strategies. Analysis of theoretical latency and timeliness for cloud-hosted AI services and edge-assisted offloading strategies. Design and development of edge-assisted offloading strategy and associated software APIs. Validation of edge-assisted offloading strategy via simulations and live demonstrations. Job Requirements A Ph.D degree in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly analytical, proactive and a team player. Strong theoretical background in wireless communications or edge computing will be advantageous. Proven track record in research and development of edge intelligence algorithms will be advantageous. Knowledge of machine learning or reinforcement learning techniques will be advantageous. Proficiency in algorithm development using Python will be advantageous

About Us The Roger Williams Institute of Liver Studies (RW-ILS) is at the forefront of delivering world-leading discovery science and translating it into impactful solutions for patients with liver disease. By working closely with local public and patient groups throughout the research journey, we ensure our innovations are relevant, transformative, and centred around patient needs. As a pioneering collaboration between the Foundation for Liver Research, King’s College London, and King’s College Hospital NHS Foundation Trust, we bridge the gap between cutting-edge science and real-world patient outcomes. Our approach integrates clinical expertise with advanced research to tackle liver disease from every angle. We are driving excellence across five research themes: Transplantation, Advanced Therapies & Regenerative Medicine Steatotic Liver Diseases Cirrhosis & Gut-Liver Axis Hepatobiliary Cancer Paediatric Hepatology & Rare Diseases About the role The Senior Lecturer/Reader/Professor in Hepatology will play a pivotal role in advancing the Faculty’s academic strategy by leading high-impact research into liver disease and contributing to the education of the next generation of scientists and healthcare professionals. This position will drive innovation through academic expertise in liver studies and translational research. The appointee will foster interdisciplinary collaborations, deliver research-led education, and mentor early-career researchers, ensuring King’s College London remains at the forefront of addressing contemporary healthcare challenges .The role will involve conducting and leading high-impact research aligned to the research themes of the Roger Williams Institute of Liver Studies (RW-ILS), while developing and maintaining an externally funded research programme. Core outputs will include: publishing high-quality research outputs in peer-reviewed journals, enhancing the Faculty’s research profile and supporting its Research Excellence Framework (REF) submission; fostering interdisciplinary collaborations within the Faculty and with external research groups, including national and international partners; providing research-led teaching across undergraduate and postgraduate programmes, including the MBBS, MSc, and PGCert courses, ensuring alignment with the Faculty’s education strategy; supervising and mentoring PhD students and early-career researchers, promoting a culture of innovation, excellence, and academic development; contributing to the design and delivery of teaching modules; actively engaging in academic administration and committee work as required, contributing to the Faculty’s strategic and operational goals. This is a full time post (35 hours per week), and you will be offered an indefinite contract. About You To be successful in this role, we are looking for candidates to have the following skills and experience: Senior Lecturer Essential criteria PhD (or equivalent) qualified in relevant subject area Demonstrable expertise in hepatology or a related field, with a history of high-quality, peer-reviewed publications Strong record of obtaining prestigious, substantial research funding/grants Evidence of teaching experience at undergraduate and postgraduate levels. Experience teaching small and large groups. Evidence of engagement with teaching delivery Proven ability to lead research projects, mentor early-career researchers, and foster interdisciplinary collaboration within academic and clinical settings Experience with data analysis techniques Desirable criteria Evidence of working with international research groups or consortia, contributing to global perspectives on liver diseases and advancing multi-centre studies Experience in integrating public and patient involvement (PPI) into research or clinical practice, enhancing the relevance and impact of research outcomes A developing national reputation in your discipline and be recognised as having made an individually significant contribution to your field and/or innovative contributions to the field Reader Essential criteria PhD (or equivalent) qualified in relevant subject area Demonstrable expertise in hepatology or a related field, with a history of high-quality, peer-reviewed publications Strong record of obtaining prestigious, substantial research funding/grants Evidence of teaching experience at undergraduate and postgraduate levels. Experience teaching small and large groups. Evidence of engagement with teaching delivery Proven ability to lead research projects, mentor early-career researchers, and foster interdisciplinary collaboration within academic and clinical settings Experience with data analysis techniques Established a national and emerging international reputation in your discipline and been recognised as having made significant and innovative contributions to your field. These contributions should have been sustained over a period of time Desirable criteria Evidence of working with international research groups or consortia, contributing to global perspectives on liver diseases and advancing multi-centre studies Experience in integrating public and patient involvement (PPI) into research or clinical practice, enhancing the relevance and impact of research outcomes Professor Essential criteria PhD (or equivalent) qualified in relevant subject area Demonstrable expertise in hepatology or a related field, with a history of high-quality, peer-reviewed publications. Strong record of obtaining prestigious, substantial research funding/grants Evidence of teaching experience at undergraduate and postgraduate levels. Experience teaching small and large groups. Evidence of engagement with teaching delivery Proven ability to lead research projects, mentor early-career researchers, and foster interdisciplinary collaboration within academic and clinical settings Experience with data analysis techniques Established a strong international reputation in your discipline and been recognised as having made significant and innovative contributions to your field. These contributions should have been sustained over a period of time Evidence of working with international research groups or consortia, contributing to global perspectives on liver diseases and advancing multi-centre studies Desirable criteria Demonstrated the ability to implement and successfully deliver initiatives and formulate strategic plans that reflect and support the priority needs of the Faculty and University. The panel will also consider any innovation, and knowledge exchange activity undertaken and its impact outside of academia. Experience in integrating public and patient involvement (PPI) into research or clinical practice, enhancing the relevance and impact of research outcomes 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 advert. 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. This post is subject to Occupational Health clearance. Grade and Salary: Senior Lecturer - £65,091 - £74,613 per annum, Reader £66,884 - £74,613 per annum, including London Weighting Allowance. Professor discussed at point of offer. Job ID: 127265 Close Date: 01-Feb-2026 Contact Person: Professor Phil Newsome Contact Details: philip.newsome@kcl.ac.uk

Description The Clinical Artificial Intelligence Lab at NYU Abu Dhabi seeks to improve patient care by developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health records and medical images, for applications pertaining to patient diagnostics and prognostics. We are seeking a Research Assistant to join the team and make significant contributions to the field. The researcher is expected to have (i) strong machine learning skills to improve model performance and robustness, and (ii) exemplary passion and motivation to pursue multidisciplinary research at the intersection of computing and healthcare. Methodologies of interest include: Multi-modal learning Foundation models, including large language models Agentic AI Multi-agent AI systems Transfer learning Self-supervised learning Federated learning The Research Assistant will be primarily based at NYU Abu Dhabi. The researcher will report directly to Dr. Farah Shamout and work in close collaboration with other researchers, PhD students, and undergraduate research assistants. The researcher will engage with our regular collaborators across the NYU campuses and local medical institutions in the UAE. Key Responsibilities Research Support the supervisor in developing and implementing the research agenda; Conduct high-quality and innovative research primarily focused on ML for healthcare; Design and implement experiments to compare proposed work with SOTA baselines; Publish research findings in high-impact journals and conferences; Communicate and present research findings at international academic gatherings; Create, maintain, and document high-quality research code for reproducibility; Maintain good practice in managing and accessing sensitive medical datasets; And collaborate with scientists within the NYU Global Network and in Abu Dhabi. Minimum Qualifications Currently has or is in the process of completing a bachelor’s or master’s degree from a recognized institution Bachelor’s/ Master’s degree in computer science, mathematics, computer engineering, or relevant technical field Demonstrable research experience involving data pre-processing and preparation for machine learning models Demonstrable research experience in conducting experiments for training and evaluating deep neural networks Knowledge of multi-modal learning, transfer learning, transformers, or self-supervised learning Experience in dealing with large medical datasets (e.g., electronic health records data or medical images) Ability to use high performance computing cluster Proficient programming experience in Python and libraries (e.g., Pytorch, TensorFlow) Experience in maintaining high-quality code on Github Experience in running and managing experiments using GPUs Ability to visualize experimental results and learning curves Effective inter-personal and team-building skills Self-motivated with an ability to work independently and in a team to get the work done Excellent communication skills (oral and written communication) Willingness to learn and confront new challenges Preferred Qualifications Bachelor’s/ Master’s thesis conducted in the area of machine learning for healthcare and related topics First-author peer-reviewed published papers (or under review) Evidence of leadership and service activities in the academic domain For consideration, applicants need to submit a cover letter, curriculum vitae with full publication list, research statement (1-page), project proposal summary (1-page), and three letters of reference, and a transcript, all in PDF format. If you have any questions, please email Prof. Farah Shamout at farah.shamout@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. Please visit our website at http://nyuad.nyu.edu/en/about/careers/faculty-positions.html for instructions and information on how to apply. 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/SexualOrientation/Gender Identity Employer UAE Nationals are encouraged to apply.