King Mongkut’s University of Technology Thonburi

The University of Surrey is a global community of ideas and people, dedicated to life-changing education and research.  We are ambitious and have a bold vision of what we want to achieve - shaping ourselves into one of the best universities in the world, which we are achieving through the talents and endeavour of every employee. Our culture empowers people to achieve this aim and to collectively, and individually, make a real difference. The role We are seeking an enthusiastic and experienced Adult Nursing Lecturer to join our academic team on a two-year full-time contract. Alongside teaching and supporting pre-registration nursing students, the successful candidate will undertake the role of Lead for Practice Placement Learning providing strategic and operational leadership for clinical placements across a diverse range of healthcare settings. The post holder will work collaboratively with NHS, social care, community, and independent sector partners to develop, enhance, and quality assure practice learning environments. They will lead initiatives to expand placement capacity, support Practice Supervisors, Practice Assessors and Academic Assessors, and ensure that student learning experiences meet professional, regulatory and university standards. The role requires a registered healthcare professional (NMC) with experience of supporting learners in practice settings, strong partnership-working skills, and a commitment to delivering excellent student experiences. The successful candidate will contribute to teaching, curriculum delivery, student support, placement quality assurance, and the continued development of practice-based education across the School of Health Sciences About you Be a current NMC registered Adult Nurse. Hold a teaching qualification aligned to Lecturer A/B level (or equivalent) (e.g. PGCertHE or equivalent). Have experience of supporting students in both academic and practice settings. Be able to work collaboratively with external partners, including NHS and care providers. Demonstrate strong communication, organisational, and interpersonal skills. Have a commitment to high-quality teaching, student support, and professional standards. How to apply to apply, please submit the following via our online recruitment portal: A full CV A supporting statement outlining how you meet the essential criteria and your experience of supporting learners in practice settings, strong partnership-working skills, and commitment to delivering excellent student experiences. You will also be asked some brief questions to help us understand your suitability for the position. If you would like an information discussion about this role please contact Dr Wendy Grosvenor (w.grosvenor@surrey.ac.uk) Interviews will be held on Wednesday 15th July. Further details Job Description

Schemes of Service: Research Division: Food, Chemical and Biotechnology Employment Type: Fixed Term As a University of Applied Learning, the Singapore Institute of Technology (SIT) works closely with industry partners to deliver translational, impact-driven research. This role supports applied food processing research projects with strong industry relevance, focusing on product development, process optimization, and project management. Key Responsibilities Lead and manage applied food processing related research projects in collaboration with Principal Investigators, Co-PIs, and industry partners. Lead applied research on mushroom-, mycelium-, and plant‑based (PB) protein ingredients, with emphasis on improving nutrition, flavour, digestibility, and techno‑functional performance. Design and execute physicochemical and biological processing strategies for protein enhancement, including thermal (UHT, ohmic heating), non‑thermal (ultrasound, high‑pressure homogenisation, microwave, pulsed electric fields), and solvent‑shifting approaches (pH and salt shifting). Evaluate and integrate green processing technologies, including deep eutectic solvents, for protein extraction, off‑taste reduction, and sustainability‑driven process optimisation. Lead the process design for scale-up fractionation and separation from bench-top, to pilot plant scale production involving centrifugation, clarification, recovery and separation of supernatant, and drying process. Support AI‑enabled data analysis, including collaboration on Artificial Neural Networks and Gaussian Process modelling, to accelerate processing optimisation. Consolidate experimental, techno‑economic, and sustainability data into robust technical evidence packages for project reporting, stakeholder engagement, and regulatory or translational decision‑making. Coordinate project timelines, milestones, budgets, procurement of consumables and equipment, and compliance with grant and institutional requirements. Prepare scientific manuscripts, technical reports, progress updates, and final deliverables for funding agencies and stakeholders. Engage and communicate effectively with internal and external collaborators to support progress meetings, reporting, and technology transfer activities. Supervise and mentor junior researchers, engineers, students, and visiting scholars involved in the projects. Support dissemination of research outcomes through conferences, stakeholder meetings, and approved communication channels. The candidate is to communicate with all relevant internal and external stakeholders as required to meet the project deliverables. Any other adhoc duties assigned by supervisor. Job Requirements PhD in Food Science, Food Technology, Chemical Engineering, or a closely related discipline. Strong Master’s degree holders with relevant experience may be considered. Strong technical background in protein functionality, structure–function relationships, and food biopolymer systems, particularly in plant‑ and fungal‑derived proteins. Demonstrated experience with food processing technologies, including thermal and non‑thermal treatments, fermentation, extrusion, or texturisation methods. Working knowledge of process optimisation tools (e.g. RSM) and familiarity with data‑driven or AI‑assisted modelling approaches is an advantage. Experience in pilot‑scale processing, scale‑up assessment, or techno‑economic evaluation of food ingredients or processes. Hands-on experience in processing trials, analytical characterization, and data interpretation. Ability to translate complex experimental outcomes into industry‑relevant insights, supporting product development, clinical study readiness, and market‑facing prototypes. Strong project ownership mindset, with the ability to balance scientific depth, cost, scalability, and industrial feasibility. Experience working with industrial collaborators, pilot-scale facilities, or product development teams is highly advantageous. Strong scientific writing skills, with experience in preparing manuscripts, technical reports, and funding-related documentation. Detail-oriented, self-motivated, and able to work independently as well as collaboratively in multidisciplinary teams. Good communication and stakeholder management skills, including liaison with vendors, suppliers, and external partners.

Job Description FACULTY OF SCIENCE DEPARTMENT OF MATHEMATICS The Department is strongly committed to producing top-class research in the areas of applied mathematics, scientific computing and statistics, while simultaneously emphasises the nurturing of students from a wide range of academic backgrounds. It receives allocation from Science Faculty Niche Research Area to establish world-class research teams to develop the necessary experimental platforms, modelling and data analysis capabilities. Research Assistant Professor (25260788) Responsibilities: The Department is recruiting one scholar at the rank of Research Assistant Professor with research interests in areas such as applied probability, spatial statistics, and stochastic processes. The appointee is expected to conduct high-impact research and engage in various scholarly activities, including securing research funding, student supervision and taking up teaching duties, if necessary. Requirements: A relevant PhD degree in probability and statistics; Demonstrate potential for excellence in research; Experience in teaching at the university level is also expected; and A promising track record in developing novel models and original methodologies is a definite advantage.  The initial appointment will be offered on a fixed-term contract up to two years. Salary will be commensurate with qualifications and experience. Application Procedure: Applicants are invited to submit their applications at the HKBU e-Recruitment System. Those who are not invited for interview 8 weeks after submission of application may consider their applications unsuccessful. Details of the University's Personal Information Collection Statement can be found at https://hro.hkbu.edu.hk/en/worklife-at-hkbu/employee-favourable-environment.html#privacy-policy. The University reserves the right not to make an appointment for the post advertised, and the appointment will be made according to the terms and conditions applicable at the time of offer. Review of applications is ongoing until the position is filled.