State University of Information and Communication Technologies

The Singapore Institute of Technology (SIT) is Singapore’s first University of Applied Learning, offering industry-relevant degree programmes that prepare its graduates to be work- and future-ready professionals. Its mission is to maximise the potential of its learners and to innovate with industry, through an integrated applied learning and research approach, so as to contribute to the economy and society. The university’s unique pedagogy integrates work and study, embracing authentic learning in a real-world environment through collaborations with key strategic partners. Its focus on applied research with business impact is aimed at helping industry innovate and grow. Targeted to be ready in 2024, SIT’s centralised campus within the larger Punggol Digital District will feature a vibrant learning environment where academia and industry will be tightly integrated with the community. SIT espouses an applied learning approach and offers degrees with a strong focus on science and technology. Our faculty work closely with industry on translational research and innovation, as well as provide consultancy on solutions to industry challenges. This well-established nexus with industry endows our graduates with deep skills and work-ready training experience – attuning them to the needs and demands of the future economy. SIT is expanding its Robotics and Embodied AI (EAI) capabilities, building a cohort of academic staff who are keen and experienced working on industry problems in relevant areas. At SIT, Robotics and Embodied AI faculty will have the opportunity to shape and lead applied research in a unique real-world environment. Located within Punggol Digital District (PDD), SIT’s purpose-built campus serves as a living lab for precinct-scale robotics test-bedding, where faculty can work with government and industry partners to develop, validate and deploy next-generation robotic systems safely and at scale. Candidates will contribute to industry-relevant research in embodied AI, simulation and digital twins, cybersecurity, robot operations and related areas, with a strong emphasis on translation into real-world applications. Through collaborations with leading robot companies and end-users, faculty will help solve practical deployment challenges, build shared digital infrastructure, and train the next generation of robotics talent for Singapore’s future economy. Responsibilities: Lead and contribute to applied research projects with industry partners and government agencies. Develop and teach Robotics and Embodied AI courses within the cluster’s programmes and across relevant interdisciplinary modules. Supervise Industry Doctorate/Masters and capstone projects in collaboration with domain faculty and industry partners. Contribute to SIT’s continuing education offerings. Serve as embodied AI mentor for existing SIT domain faculty through joint projects and co-supervision mechanisms. Qualifications: PhD in Robotics, Mechanical/Electronics Engineering, Computer Science, or a relevant domain with demonstrated embodied AI research experience. Equivalent industry experience may also be considered. Technical expertise and track record in the following areas (ideally at least two): Policy Learning and Robotics Control: Imitation / reinforcement learning, generative policies, residual learning, cross-embodiment generalisation. Robotics Data Engineering: Data capture, synchronisation, calibration, evaluation harnesses and simulation data pipelines Foundation Models & World Models for Robotics: VLA grounding, planning interfaces and world-model reasoning for robots State Estimation, Perception and Sensor Fusion: 3D scene understanding, diagnostics, active and manipulation-centric perception System Integration, Deployment & RobotOps: ROS2 systems integration, runtime robustness, safety and field deployment engineering Swarm Robotics & Multi-Agent Systems: Decentralised coordination, shared mapping and resilient communications Fleet Management & Remote Operations: Mission control, tele-operation, network resilience and lifecycle operations Cyber-Physical Security & Trustworthy Robotics: Threat modelling, resilience, incident response, AI ethics and data privacy Experience applying embodied AI to real-world use areas will be advantageous, such as (non-exhaustive): Facility Management Healthcare Advanced Manufacturing Urban Systems Biotechnology & Chemical Engineering Demonstrated leadership and evidence of working on industry/society-defined problems Strong connections with international partners and organisations will be advantageous. Experience with industry research collaborations, applied research grants, and/or system deployment Established thought leadership and/or professional standing e.g. publications in top journals and keynotes, in addition to non-publication outputs and impact such as open-source tools, technical reports, patents, deployed systems Demonstrated track record of cross-disciplinary collaborations Ability to communicate clearly with domain experts, industry practitioners and general public What SIT offers: An applied research environment, working together with industry partners, to tackle real-world problems SIT values applied research impact and evaluates faculty accordingly on how their research had made a difference to society or industry Opportunities to work on a coherent robotics & embodied AI research agenda with colleagues across disciplines Access to Punggol Digital District ecosystem as testbeds for applied research A meaningful role in building Singapore’s robotics & embodied AI research capability at a pivotal moment Singapore’s exceptional quality of life, competitive personal tax environment, and position as Asia’s leading research and innovation hub How to apply: Candidates should submit the following: Curriculum vitae including grants, outputs (code, datasets, patents, technical disclosures) and publications Cover Letter Research statement (up to 2 pages) addressing your applied AI research programme, how it connects to SIT’s cluster context, and your experience with industry-connected research Teaching statement (up to 1 page) addressing your approach to applied learning Three highlights of research outputs with a brief explanation of each output’s impact

Organisation: Cranfield University Faculty or Department: Executive Office Based at: Cranfield Campus, Cranfield, Bedfordshire Hours of work: 37 hours per week, normally worked Monday to Friday. Flexible working will be considered. Contract type: Permanent Salary: Full time starting salary is normally in the range of £48,760 to £58,664 per annum, with potential progression up to £71,050 per annum Apply by: 16/06/2026 Role Description About the Role This is a senior strategic role responsible for ensuring Cranfield University remains fully compliant with its national security obligations across research, education, partnerships, people, estates and information security. Reporting to the Pro Vice-Chancellor – Education & Research, you will lead the development and implementation of the University’s national security strategy, policies and assurance framework, working closely with internal stakeholders and external government bodies. The role will support the University’s National Security Committee and oversee compliance relating to areas including trusted research, export controls, personnel security, international collaboration and wider legislative requirements. About You You will be educated to degree level or equivalent experience and will have significant experience in a senior security or national security-related role. You will have expertise in developing and implementing security policies, procedures and assurance frameworks, alongside experience delivering complex security related projects. You will have strong knowledge of the UK defence and security sector, government security requirements and national security legislation, together with excellent communication and stakeholder engagement skills. Experience of working within a UK Defence or Security organisation, government environment or Higher Education institution would be advantageous. You will be highly organised, proactive and resilient, with the ability to influence and collaborate effectively across a wide range of stakeholders. Holding current DV Security Clearance, or willingness and eligibility to obtain this, is essential. About Us As a specialist postgraduate university, Cranfield’s world-class expertise, large-scale facilities and unrivalled industry partnerships are creating leaders in technology and management globally. Learn more about Cranfield and our unique impact here. The Executive Office provides strategic leadership and governance across the University, supporting delivery of Cranfield’s mission, institutional priorities and external partnerships. This role sits at the centre of an evolving and increasingly important national security agenda, supporting Cranfield’s long-standing relationship with the UK defence and security community. Our Values and Commitments Our shared, stated values help to define who we are and underpin everything we do: Ambition; Impact; Respect; and Community. Find out more here. We aim to create and maintain a culture in which everyone can work and study together and realise their full potential. We are a Disability Confident Employer. We are committed to actively exploring flexible working options for each role and have been ranked in the Top 30 family friendly employers in the UK by the charity Working Families. Find out more about our key commitments to Equality, Diversity and Inclusion and Flexible Working here. Working Arrangements Collaborating and connecting are integral to so much of what we do. Our Working Arrangements Framework provides many staff with the opportunity to flexibly combine on-site and remote working, where job roles allow, balancing the needs of our community of staff, students, clients and partners. How to apply For an informal discussion about this opportunity, please contact Charly Guilford, Business Partner – People and Culture on (E): charly.guildford@cranfield.ac.uk Please do not hesitate to contact us for further details on E: hrrecruitment@cranfield.ac.uk. Please quote reference number 5320. Closing date for receipt of applications: 16 June 2026 Please note that we reserve the right to close this advert prior to the stated closing date should we receive sufficient numbers of applications. Therefore, we would encourage you to complete and submit your application as soon as possible.

About UM6P: Mohammed VI Polytechnic University is an institution dedicated to research and innovation in Africa and aims to position itself among world-renowned universities in its fields The University is engaged in economic and human development and puts research and innovation at the forefront of African development. A mechanism that enables it to consolidate Morocco's frontline position in these fields, in a unique partnership-based approach and boosting skills training relevant for the future of Africa. Located in the municipality of Benguerir, in the very heart of the Green City, Mohammed VI Polytechnic University aspires to leave its mark nationally, continentally, and globally. About IWRI: The International Water Research Institute (IWRI) provides research, education, and innovation in the fields of water and climate. In order to face the next challenges. IWRI seeks to rethink and adapt research development, innovation, and training to new paradigms. It is an institute that outlines forward-thinking pathways to address water issues in a systemic manner in Africa. IWRI's vision is to Lead and develop integrated research and processes for Water & Climate concerns in Africa. We act as an African water hub through strategic cooperation and partnerships. We share comprehensive and diverse expertise to provide scientific information by focusing on four pillars: Integrated water resources management, Climate change and adaptation, Hydroinformatics, and Water technologies. Position Summary: The International Water Research Institute (IWRI) of the College of Agriculture and Environmental Sciences (CAES) at UM6P invites applications for a postdoctoral researcher position in hybrid machine learning-physics based modeling of hydroclimatic extremes in data scarce regions. The postdoctoral researcher will develop innovative hybrid machine learning-physics based modeling approaches to improve the understanding and prediction of hydroclimatic extremes in data-scarce regions, with a primary focus on Morocco. The position aims to advance methods that integrate data-driven algorithms with physically based hydrological and climate models under conditions of limited observations, while ensuring that the resulting tools are both scientifically robust and operationally relevant. A key component of the role is the translation of model outputs into actionable information for stakeholders, particularly water resource managers and planning authorities, and the evaluation of long-term water management strategies aimed at mitigating water scarcity. The project also includes assessing the transferability of the developed approaches to other regions facing similar constraints.  Scientific context: Hydroclimatic extremes such as droughts and floods are intensifying under climate variability and change, particularly in regions where observational data are sparse and monitoring systems are limited. In such context, traditional physically based models are often constrained by insufficient data, while purely data-driven approaches may lack physical consistency and generalizability. Hybrid modeling frameworks that combine machine learning with process-based understanding offer a promising pathway to overcome these limitations. Morocco provides a compelling case study, given its pronounced hydroclimatic variability, increasing water stress, and ongoing investments in large-scale water management strategies. However, significant challenges remain in reliably predicting extreme events and assessing long-term adaptation options under deep uncertainty and data scarcity. Research Scope: The project will focus on the development of a new generation of hybrid modeling approaches that couple advanced machine learning methods with hydrological and/or climate models. Emphasis will be placed on designing approaches that are robust to data scarcity through the integration of heterogeneous data sources, including remote sensing products, reanalysis datasets, and sparse in-situ observations, as well as techniques such as transfer learning and uncertainty quantification. The research will address the detection, attribution and prediction of hydroclimatic extremes under non-stationary conditions and evalaute model performance over Morocco as a primary testbed. A central components of the work will invovle translating model outputs into decision-relevant indicators and assessin the feasibility and robustness of long-term water maangemnt strategies currently under consideration. The transferability of the developed methods to other regions will also be systematically investigated. Candidate Profile: PhD in hydrology, climate science, geosciences, applied mathematics, computer science or related field Expertise in mahcine learning, physically based modeling or hybrid approaches combining boths Strong programming skills (Python, MATLAB, Fortran, or similar) and familiarity with ML frameworks. Experience with hydroclimatic data, including remote sensing products, reanalysis datasets and/or in-situ observations Knowledge of uncertainty quantification, data assimilation, or transfer learning is a strong advantage. Proven ability to handle HPC environements is an added asset Demonstrated ability to develop and evaluate models under data-scarce conditions. Ability to communicate results to both scientific and non-technical stakeholders, including water managers and policy actors.