Sault College

At the heart of SIT’s mission is to nurture industry-ready graduates equipped with deep technical expertise and transferable skills to tackle tomorrow’s challenges. SIT collaborates with industry in our education, while benefitting them with our talent supply and collaborative research achievements. The University’s unique applied learning pedagogy integrates work and study, embedding authentic learning experiences within real-world environments. Through strategic partnerships forged by our faculty with industry, learners bridge theoretical knowledge with practical application in and out of the classroom. Such active & authentic learning opportunities ensures graduates step into their careers with applicable skills and competence. In research, SIT faculty aims to bridge knowledge creation and utilisation. Our faculty collaborates closely with industry on translational research and innovation with focus on addressing pertinent industry challenges to impact businesses.  The Singapore Teaching and Academic Research Talent (START) Scheme is co-funded by the Ministry of Education (MOE) and SIT to encourage and support outstanding young Singaporeans interested in pursuing an academic career at SIT. The Applied Research Fellowship aims to provide doctoral candidates who are about to complete or have recently completed their studies an opportunity to engage in advanced training and/or research at an overseas university for one year.  Besides financial support, awardees will also receive academic mentorship.  Upon completion of the Fellowship, awardees will be considered for Assistant Professorship. Eligibility and Selection Criteria Singapore citizen  Doctoral candidates who have recently completed or are about to complete their studies in a discipline under the supported areas for START below  Excellent academic record plus a high degree of proficiency and motivation for selected research area  Have been accepted or have applied for a postdoctoral training at a leading overseas university in a research area that is aligned with SIT’s supported areas  A keen interest in an academic career Value of Fellowship The Fellowship provides  Monthly stipend  Overseas maintenance allowance  Return economy airfare  Conference and fieldwork grants  Overseas medical insurance  Fellows will also each be assigned a SIT faculty mentor throughout their post-doctoral training and have opportunities to participate in faculty development programmes. The fellowship is tenable for one year. On an exception basis, a two-year programme may be supported. Service Commitment One year for every year of sponsorship. Application Process Applications are open throughout the year via the various links below. Applications received before 15 January 2026 will be considered for the 2026 intake.   Interview by the respective clusters for shortlisted applicants will be conducted throughout the year.   Final Interview by the Panel for shortlisted applicants for the 2026 intake will commence in Mid-March to End April 2026.   Awards will be finalised by July 2026. Supported Areas for START - Engineering   Energy Resilience: Power electronic converters for distributed energy resources and microgrids; High voltage DC transmission and distribution components and systems; Electric propulsions systems for land, sea and air; Wide bandgap solid-state protective devices.  Sustainable Infrastructure Engineering and Maintenance: Construction technology, Tunnel engineering, Integrated BIM for Civil and MEP design optimisation; Non-destructive testing and prognostic maintenance for infrastructure rejuvenation and life extension.  Sustainable Maritime Engineering: Ship design and optimisation towards maritime decarbonisation; maritime battery room design for safety; intelligent ship and operations; autonomous vessels and systems.

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​

At the University of Vienna more than 10,000 personalities work together towards answering the big questions of the future. Around 7,500 of them do research and teaching, around 2,900 work in administration and organisation. We are looking for a/an University assistant predoctoral/PhD Candidate Optical Quantum Computing and Machine Learning 51 Faculty of Physics Startdate: 01.02.2026 | Working hours: 30 | Collective bargaining agreement: §48 VwGr. B1 Grundstufe (praedoc) Limited until: 31.01.2030 Reference no.: 5037 We invite you to join the Operational Quantum Information Team (Dakić Group) to work on topics in quantum information theory and quantum technologies, with a special focus on optical quantum computing and machine learning with nonlinear mechanical systems. Your personal sphere of influence: As a university assistant (praedoc) in this 4-year position, you will be part of the Operational Quantum Information Team around Professor Borivoje Dakić. Our team is part of the Quantum Optics, Quantum Nanophysics, and Quantum Information group of the Faculty of Physics. We are a member of the Vienna Center for Quantum Science and Technology (VCQ), one of the largest quantum hubs in Europe, and of the Austrian Cluster of Excellence (quantA), advancing basic research in quantum sciences, aiming to expand the frontiers of knowledge and thus being the engine for future innovations. You will also benefit from being a fellow of the Vienna Doctoral School in Physics (VDSP), being part of a thriving community with more than 100 quantum scientists on premises and about 300 quantum researchers in Vienna. The Dakić group is an international team of young scientists (Master / PhD / Postdoc). Our expertise lies in quantum foundations, quantum information theory and quantum technologies. For additional information, please visit: https://dakic.univie.ac.at/. Your future tasks: You will actively participate in research, teaching and administration. This means: You are involved in a well-funded research project on the advertised research topics. You will present your research plan to the faculty and complete a dissertation agreement within 12–18 months. This will be reviewed and adapted on an annual basis. You will work on your dissertation and towards its completion in time. We expect a large degree of independence paired with a high level of social awareness, as the goal will only be achieved in a team. You will contribute to teaching (lab courses, exercise classes) within the provisions of the collective bargaining agreement. You will fulfil some administrative tasks, contributing to the success and self-organization of the group in research, teaching and administration. You will continuously stay informed about the state of the art in your field. You will contribute to outreach by publications, conference presentations and public activities. This is part of your personality: We expect a strong candidate with the following requirements: You have completed your Master’s degree or Diploma in Physics, Mathematics, Computer Science or a closely related field, ideally with a strong focus on quantum computing and numerical simulations. Experience in data-reuploading quantum algorithms, optical quantum computing and quantum machine learning (highly desirable). Experience in machine-learning schemes based on arrays of nonlinearly interacting mechanical oscillators (highly desirable). Experience in programming skills (e.g. Python, Qiskit, MATLAB, C, numerical simulations). You have an excellent command of written and spoken English. What we offer: Inspiring working atmosphere: You are part of an international academic team in a healthy and fair working environment. Good public transport connections: Your workplace in the center of beautiful Vienna is easily accessible by public transport. Potential for development: Success in life depends on what you make of it, but if you are ambitious and successful, there are plenty of opportunities to connect you to all relevant top research groups in the world in quantum information, quantum technologies and machine learning. Internal further training & coaching: The Vienna Doctoral School as well as the Department of Human Resources offer plenty of opportunities to grow your skills in over 600 courses to choose from – free of charge. Fair salary: The basic salary of EUR 3.714,80 (full-time basis, 14x p.a.) increases if we can credit professional experience. The employment duration is 4 years. Initially limited to 1.5 years, the employment relationship is automatically extended to 4 years if the employer does not terminate it within the first 12 months by submitting a non-extension declaration. Equal opportunities for everyone: We look forward to diverse personalities in the team! It is that easy to apply: Please send us: Your scientific curriculum vitae. A statement on your research interests for the future (motivation letter), with particular emphasis on your experience in optical quantum computing and data-reuploading algorithms, and machine-learning schemes based on arrays of nonlinearly interacting mechanical oscillators. Contact information of two referees. Your Bachelor’s and Master‘s degree certificates and transcripts. If you have any content questions, please contact: Borivoje Dakic borivoje.dakic@univie.ac.at We look forward to new personalities in our team! The University of Vienna has an anti-discriminatory employment policy and attaches great importance to equal opportunities, the advancement of women and diversity. We lay special emphasis on increasing the number of women in senior and in academic positions among the academic and general university staff and therefore expressly encourage qualified women to apply. Given equal qualifications, preference will be given to female candidates. University of Vienna. Space for personalities. Since 1365. Data protection Application deadline: 01/06/2026 (MM-DD-YYYY) Prae Doc