RWTH Aachen University

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 Postdoctoral Researcher 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 Postdoctoral Researcher 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 methodology development for healthcare; Generate new high-impact ideas based on gaps and limitations of the state-of-the-art (SOTA); 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; Assist the supervisor in the preparation of grant applications (as appropriate); And collaborate with scientists within the NYU Global Network and in Abu Dhabi. Training & professional development Attend trainings and workshops for career development; Mentor PhD students and undergraduate research assistants (as appropriate); Actively participate in events and committees at NYU Abu Dhabi, such as the Postdoctoral Council Steering Committee; Gain experience in applying for local research grants (subject to eligibility); And transition to independence to pursue a career of choosing following the appointment. * The researcher will create a personalized training and development plan with the supervisor. Minimum Qualifications Currently has or is in the process of completing a PhD, MD/PhD, DPhil or equivalent terminal degree from a recognized institution (no more than 5 years since completing the doctoral degree) Doctoral research in the area of machine learning and artificial intelligence Bachelor’s/ Master’s degree in computer science, mathematics, computer engineering, or relevant technical field First-author peer-reviewed published papers (or under review) Proficient programming experience in Python and libraries (e.g., Pytorch, TensorFlow) with several years of practice 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 Doctoral research conducted in the area of machine learning for healthcare and related topics Deep knowledge of multi-modal learning, transfer learning, foundation models, and 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 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.

Description As part of the Electrical Engineering program of the Engineering Division and the Center of Artificial Intelligence and Robotics at NYU Abu Dhabi the group of Prof. Kostas J. Kyriakopoulos seeks to improve the autonomy of Field Robotic systems by fusing control theoretic and machine intelligence approaches. Formal models are directly applied in real experimental facilities. Marine Robotics is our current emphasis, without excluding candidates with prior experience on Aerial or Ground Systems. We are seeking a Post-Doctoral associate to join our expanding team and make significant contributions to the field. The researcher is expected to have (i) strong engineering skills to find innovative and cost-effective means to improve our research, and (ii) exemplary passion and motivation to enhance our multidisciplinary research at the intersection of control theory and machine intelligence. Methodologies of interest include: Robot modelling, Nonlinear and Optimal control, Reinforcement learning, and Data-driven modeling and control. The Post-Doctoral associate will be based at NYU Abu Dhabi and will directly report to Prof. K.J.Kyriakopoulos in close collaboration with other researchers, PhD students, and undergraduate research assistants. The Post-Doctoral associate will engage with our regular collaborators at local institutions in the UAE and abroad. Key responsibilities Conduct high-quality and innovative research primarily focused on Control theory and ML methodologies for Field Robotics; Support the supervisor in developing and implementing the research agenda; Reproduce results of the state-of-the-art (SOTA) methods; Design and implement experiments on real platforms operating outdoors, to compare our proposed work with SOTA baselines; Contribute to the preparation of manuscripts for publication in high-impact journals and conferences; Create, maintain, and document high-quality research code for reproducibility; and Collaborate with scientists within the NYU Global Network and in Abu Dhabi. Minimum Qualifications Possessing a Doctoral degree from a recognized institution in Electrical, Mechanical, Naval or Aerospace Engineering. First-author peer-reviewed published papers (and/or under review) Demonstrable research experience involving integration of hardware and software of robotic systems. Demonstrable research experience in conducting experiments for field robotic systems Proficient programming experience in embedded, real-time software in C/C++ and Python with several years of practice Experience in maintaining high-quality code on Github Ability to visualize experimental results 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 The appointment will be for two (2) years with the option to renew further depending on performance. The terms of employment are very competitive and will include housing and travel subsidies. Applications will be accepted immediately and candidates will be considered until the position is filled. This position is not located in the United States. You must be willing to relocate to Abu Dhabi, United Arab Emirates. To be considered, all applicants must submit a cover letter, up-to-date CV, research statement (1-page), a transcript, and at least two letters of recommendation, all in PDF format on or before July 1, 2025. If you have any questions that are not answered in the job advert, please email: kk4812@nyu.edu and include [Application for postdoctoral researcher] in the subject line. 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.

About Us ​​The Digital Health Hub Training Manager will play a key leadership role within the EPSRC-funded King’s Health Partners Digital Health Hub (KHP DHH), contributing to the professional services leadership of the Hub’s training arm. The role supports the delivery of skills development for individuals working at the healthcare-industry interface, fostering collaboration between digital innovators and the healthcare workforce to address real-world challenges in digital health. Sitting within a collaborative, multi-disciplinary environment, the Training Manager will work closely with colleagues across the Hub’s core pillars (Training, Co-design, Translation, and Acceleration) to ensure impactful and integrated training delivery aligned with the Hub’s overarching goals.  ​​About the role This role is an exciting opportunity to contribute to the professional services leadership of our EPSRC-funded King’s Health Partners Digital Health Hub (KHP DHH) as the Training Manager.  The training component of this Hub focuses on identifying and delivering the skills needed to train problem solvers who address real-life challenges at the healthcare–industry interface. The goal is to support the development of proactive individuals who can use relevant data and technologies to tackle real problems in digital health. Digital innovators and the healthcare workforce work together in a multi-disciplinary environment to develop safe and scalable solutions. The training arm of the Hub works collaboratively with the other Hub arms, including AI training, co-design strategies, entrepreneurship, industrial partner engagement, Patient and Public Involvement & Engagement (PPIE), digital health innovation, and the research pilots embedded in the Hub. The four core pillars are Training, Co-design, Translation & Acceleration.  Organised and delivery-focused, you will join an established team and bring experience in gathering, interpreting, and presenting data to demonstrate impact. Experience of matrix working would be beneficial, as the programme facilitates collaborative efforts to identify and overcome barriers to effective integration and translation across disciplines. You will work closely with subject matter experts and the learning technologist to maintain and enhance existing asynchronous training resources, as well as create new engaging materials for a range of audiences in digital health. The role also supports the delivery of in-person training, from advertising and bursary coordination to post-course feedback collection.  The successful candidate will collaborate with the learning technologist to understand the learning objectives of course participants and engage with supporters, patients, and the public in workshops led by participants. These workshops provide opportunities to share learning experiences and offer feedback on the structure and content of the taught material.  Onsite working will be required for effective collaboration across the Digital Health Hub, with the expectation that the successful candidate will work onsite at least three days per week.  This is a full time post (35 hours per week), and you will be offered ​a fixed term​ contract until 31.03.27. About You ​​To be successful in this role, we are looking for candidates to have the following skills and experience:  Essential criteria ​Strong project/programme management experience, including good IT skills (Microsoft suite). ​A degree in a science or health-related field, or relevant experience, and familiarity with medical/scientific/AI terminology. ​Customer focused, with excellent communication skills both verbal and written: ability to write coherently, and in good English, to a range of audiences across a range of academic disciplines. ​Proactive, ability to work independently, problem solve and use initiative. ​Experience of managing relationships with a range of stakeholders. ​Experience of impact/non-financial outcomes measurement, analysis and reporting ​Experience with communication strategies, such as effective use of social media and websites ​Budget management experience.  ​Desirable criteria ​Knowledge of AI, and knowledge of evaluation and impact measurement techniques and analysis. ​Marketing and market research experience. ​Experience of designing or commissioning education or learning events. ​Web design and UX skills. ​Line management experience and experience of matrix working. ​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: £53,947 - £63,350 per annum, including London Weighting Allowance Job ID: 134826 Close Date: 11-Jan-2026 Contact Person: ​Professor Rebecca Oakey Contact Details: Rebecca.oakey@kcl.ac.uk​