West African Union University

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.  Job Details This Research Fellow will contribute to the UrEco 2030+ project: “Optimizing Urban Ecosystem Services Model for Urban Climate and Biodiversity in Singapore towards 2030 and Beyond.” This position requires experience in Geographic Information Systems (GIS) and related fields, with added expertise in ecosystem services assessment, ecological engineering, social sciences, policy making, environmental science, and/or urban environmental issues at the policy–academic interface. This position is ideal for an early- or mid-career researcher with experience in GIS or remote sensing who seeks to apply and expand their expertise in a fast-paced, interdisciplinary research environment. The successful candidate will work with leading researchers and contribute to cutting-edge research and policy dialogues at the intersection of blue–green infrastructure, tropical urban ecosystem services, and urban resilience (covering themes such as urban flooding, thermal cooling, recreation, and biodiversity). The work includes Local Climate Zone (LCZ) classification and collaboration with Japanese university partners for integrated macro- to micro-scale analysis. As part of understanding the ecosystem services that are involved in Singapore, the successful candidate will also be expected to perform some field-based data collection during the duration of the project. Key Responsibilities Participate in and manage the research project with Principal Investigator (PI), Co-PI and the research team members to ensure all project deliverables are met.  Identify, simulate, and analyse ecosystem service models using GIS, remote sensing, and field data. Manage, process, and analyse ecological and socio-economic datasets to develop and calibrate high-accuracy ecosystem service models. Conduct literature reviews and synthesize findings into conceptual frameworks and research designs. Support cross–work package integration, particularly in developing tools for blue–green infrastructure policy and decision-making. Perform quantitative and qualitative data collection, analysis, and visualization. Draft and edit research reports, policy briefs, and academic manuscripts. Contribute to project management, workshop organization, and stakeholder or policy dialogues. Be involved in regular field work data collection and to perform environmental and biodiversity surveys (fish, birds and insects) as part of a research team.  To communicate and liaise with any internal and external stakeholders to ensure project deliverables are met. Any other ad-hoc duties assigned by Supervisor. Job Requirements PhD in Geography, GIS, Remote Sensing, Environmental Science, Earth Science, or related disciplines. Strong working knowledge of GIS platforms (e.g., ArcGIS, QGIS) and spatial data analysis techniques. Training or demonstrated experience in remote sensing, spatial data collection, and thematic mapping. Proficiency in data analysis software (e.g., R, MATLAB, SPSS, Primer, Python). Experience with analytical techniques such as ANOVA, PCA, Regression, and Multidimensional Scaling (MDS). Experience in ecosystem service identification and analysis is highly advantageous. Excellent data management, research design, and reporting skills. Strong communication and presentation skills in English. Highly organized, proactive, and capable of working both independently and within multidisciplinary teams. Additional Note: While prior experience in ecosystem service modelling and simulation is not mandatory, it will be considered a strong advantage. Candidates with a solid GIS or remote sensing background who demonstrate interest in applying their skills to ecosystem service assessment are encouraged to apply. The project team will provide on-the-job training and guidance in ecosystem service modelling tools (e.g., InVEST and related software) to support skill development and ensure effective integration across research tasks. Key Competencies Integrates GIS, remote sensing, and environmental data for spatial modelling. Proficient in or able to learn ecosystem service software (e.g., InVEST, ARIES). Strong analytical, problem-solving, and data interpretation skills. Effective in research design, reporting, and scientific communication. Works independently and collaboratively in multidisciplinary teams. Demonstrates initiative, adaptability, and sound research ethics.

About us Recently re-founded, the Department of Engineering is rapidly expanding into a world-class research and teaching department. Research currently focuses on computational engineering, information processing systems, robotics, telecommunications, and biomedical engineering, but we are looking to establish new research themes. This post will be affiliated with the computational engineering research group within the department.  We offer both undergraduate and postgraduate teaching, with a distinctive approach, combining both traditional teaching methods with modern, project-based learning, catering for the needs of our students and the industries in which they will work.  As a new department we have invested in new laboratories and maker space at the centre of the Strand campus in the heart of central London.  For more information: https://www.kcl.ac.uk/engineering About the role This role will support the delivery of a mesh generation project, funded under a recent major £7m EPSRC Programme Grant REMODEL: Advancing Parallel Mesh Generation and Geometry Representation to Enable Industrially Relevant, High-Fidelity Simulations. The goal of REMODEL is to make major advances in mesh generation and CAD geometry to enable large-scale exascale-capable simulations for the new UK national supercomputer.  The successful candidate will work within Prof. David Moxey’s group at King’s, together with the wider REMODEL project team (Swansea University, Imperial College London, EPCC and Queen’s University Belfast), to advance adaptive mesh refinement: the ability to dynamically change resolution as large-scale simulations progress, whilst preserving the geometric representation of the project. You will work within a leading group in high-order methods: a class of finite element methods that is now leading the way for future computational fluid dynamics simulations. Specifically, our group develops the Nektar++ spectral/hp element framework (www.nektar.info), and its mesh generation tool NekMesh. The successful candidate will be expected to lead developments of both tools, working towards integrated mesh-solver cycles and enable large-scale parallel simulations that adapt the mesh to fit the underlying geometry. They will also provide NekMesh with the user-focused development required to get this presently-specialist tool into the hands of general practitioners.  The successful candidate will also help to represent the developments at King’s and work closely with the REMODEL partners in academia, as well as industrial partners. This is a full time contract (35 Hours per week), offered on a fixed term contract for two years. Research staff at King’s are entitled to at least 10 days per year (pro-rata) for professional development. This entitlement, from the Concordat to Support the Career Development of Researchers, applies to Postdocs, Research Assistants, Research and Teaching Technicians, Teaching Fellows and AEP equivalent up to and including grade 7. Visit the Centre for Research Staff Development for more information. About you To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria Have, or be about to obtain, a PhD or equivalent qualification/experience in a related field of study (e.g. applied mathematics, computational engineering, scientific computing, etc). Strong scientific computing background, with experience of different architectures (e.g. CPUs/GPUs) and their use in high-performance computing through shared or distributed parallel programming (e.g. OpenMP, MPI). Strong programming ability in C++ or a related language. Experience in working as part of a research team and ability to collaborate with external partners. A track record of publications and research appropriate to the candidate’s career stage. Excellent organisation ability and written and verbal communication skills. Desirable criteria Knowledge and/or experience in high-order methods and/or mesh generation is highly desirable. Experience with the Nektar++ spectral/hp element framework and its mesh generator, NekMesh. Experience of postgraduate supervision. 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. * Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award of their PhDs will be considered. In these circumstances the appointment will be made at Grade 5, spine point 30 with the title of Research Assistant. Upon confirmation of the award of the PhD, the job title will become Research Associate and the salary will increase to Grade 6. 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. Interviews are due to be held in the week commencing 26th January 2026. Grade and Salary: £45,031 - £48,607 per annum, including London Weighting Allowance Job ID: 133865 Close Date: 21-Jan-2026 Contact Person: Professor David Moxey Contact Details: David.moxey@kcl.ac.uk

Bring learning to life by supporting world-class teaching, research, and simulation in health sciences Are you a hands-on technical professional with strong laboratory or clinical-skills experience, and a passion for supporting teaching, research, and innovative digital technologies? This is a fantastic opportunity to join the Division of Health and contribute to the delivery of high-quality learning experiences that help shape the next generation of health professionals Ngā kōrero mō te tūranga - About the role As a Technical Officer in the Division of Health, you’ll deliver high-quality technical support that underpins our teaching and research in Health Science from applied sciences and clinical skills to simulation and cutting-edge digital technologies. Your primary focus will be on clinical skills and simulation technologies, including the set-up and operation of high-fidelity manikins, task trainers, virtual-patient platforms, AV systems, and VR/AR devices. You will also support applied science laboratories, working collaboratively as part of a team of Technical Officers to ensure seamless delivery across the Division. While you’ll have your own focus area, you’ll also share knowledge and responsibilities across the team, particularly with colleagues in applied sciences, ensuring our staff and students receive seamless, expert support at every stage. Salary will be in the range of $71,275 to $84,695 per year, prorated based on skills, knowledge and experience brought to the position. This is a one-year fixed-term 1 FTE parental cover role (37.5 hours a week) based at our Hillcrest Campus. For more information on the role please see the position description. All applications must be submitted through the online portal, emailed applications will not be accepted. Ko wai koe? - Who are you? You are an experienced technical professional with at least five years’ experience in a clinical skills, health science, or laboratory-based role. You bring strong practical skills in operating and maintaining laboratory equipment, clinical devices, and/or simulation technologies. You will demonstrate: Hands-on technical capability with scientific and clinical equipment Experience troubleshooting, calibrating, installing and maintaining instruments Strong ICT capability, including digital tools, data management and AV/VR technologies Experience supporting teaching and/or research environments Excellent communication skills, and the ability to support staff and students in real time Strong organisational and time-management skills, including project coordination Knowledge of health and safety requirements and laboratory compliance Flexibility to support varied teaching schedules and operational needs A relevant tertiary qualification (Master’s degree desirable) Preferred candidates will also bring experience in: Simulation manikins and scenario programming VR/AR and digital learning technologies AV/IT systems for teaching and simulation You are a strong team player, collaborative, proactive, customer-focused, and committed to continuous improvement. Ko wai mātou? - Who are we? The Division of Health is committed to achieving better, fairer health outcomes across Aotearoa through high-quality teaching, innovative research, and partnerships with Māori, Pacific and community organizations. Our programmes span Biomedical Sciences, Health Promotion, Healthy Active Living, Human Performance Science, Midwifery, Nursing, Pharmacy and Sport Development and Coaching. A major strategic focus is the establishment of the New Zealand Graduate School of Medicine, opening in 2028. You will join a dynamic technical team that supports state-of-the-art laboratories, clinical simulation facilities, and digital-learning technologies, all designed to enrich student learning and enhance research capability. He aha ngā take me tono mai ai koe? - Why should you apply for this position? This is an exciting opportunity to play a key role in supporting the development of future health professionals. You will work with new and emerging technologies, contribute to meaningful teaching and research, and be part of a collaborative and forward-thinking Division. Our University stands proudly on the world stage as a provider of future-focused, international education and an active player in global research. Our rankings reflect these strengths. Working with us means you’ll enjoy a satisfying work environment with many benefits. The University of Waikato is distinctive for the diversity of its staff and students and encourages applicants with the relevant capabilities from all backgrounds to apply. Applicants must have the legal right to live and work in NZ in accordance with the NZ Immigration regulations which can be found here. Ko te Tangata - For the People The University of Waikato prides itself on the quality of its engagement with the communities that it serves, the provision of a world-class education and the national and international impact of its research. Our policies are guided by the principles of the Treaty of Waitangi and equal opportunity for all. E herea ana te Whare Wānanga ki te kaupapa kia whakaratohia te mea angitū ōrite ki ngā tāngata katoa. Applications close on 18 January 2026. Requisition number: 1003246