Foundation for Professional Development (FPD)

The Role The role focuses on advancing research in explainable and trustworthy machine learning, with a particular emphasis on mechanistic interpretability and its application to healthcare data. The successful candidate will contribute to understanding how modern machine learning models represent information internally and how their predictions can be made transparent, reliable, and clinically meaningful. This work will involve developing and applying interpretability techniques to machine learning systems used in healthcare contexts, including tasks such as risk prediction, clinical decision support, and the analysis of complex biomedical datasets. The research environment is highly interdisciplinary, bringing together expertise from machine learning, statistics, data science, and healthcare research. The successful applicant will be expected to design and implement analytical and interpretability frameworks to investigate the internal representations and decision-making processes of machine learning models. This includes developing and applying techniques such as feature attribution, representation analysis, causal probing, and mechanistic circuit analysis. The postholder will also develop predictive models using modern deep learning frameworks (e.g., PyTorch) and evaluate them with a focus on interpretability, robustness, and real-world applicability in healthcare settings. The role also involves developing reproducible research software and scalable data analysis pipelines in Python for machine learning and interpretability research. These tools will support systematic investigation of model behaviour and enable robust experimentation on large and complex datasets relevant to healthcare and biomedical research. The postholder will be expected to contribute actively to high-quality research outputs, including peer-reviewed publications in leading machine learning and interdisciplinary venues, open-source software tools, and collaborative research initiatives. The successful candidate will also contribute to the preparation and development of research grant proposals, supporting the group's strong track record of successful funding and helping to expand its research portfolio in explainable and trustworthy AI for healthcare.

The University of Surrey is an international University with a world class teaching and research profile that is innovative, forward thinking and achieving notable results. Our research seeks to address global challenges, drive innovation, and deliver real-world impact. In the most recent UK Research Excellence Framework (REF2021), our research was ranked in the UK top 20 for research outputs. The University offers excellent multidisciplinary facilities within which to advance your career. In the School of Veterinary Medicine, you will have the opportunity to work with experts from world class NHS hospitals and veterinary institutes. We are seeking to recruit a Senior Lecturer or Associate Professor (Reader) in Predictive In Vitro Models to strengthen the University’s leadership in technology-driven biomedical research and advance our advance the 3Rs agenda. As a Senior Lecturer/Associate Professor, you will be expected to develop and lead a significant externally funded programme of research in line with the Faculty of Health and Medical Science’s mission of sustainably improve the health and wellbeing of humans and animals, and their environments through new knowledge and its application to the design, development and delivery of responsible innovation and impact. About the role Within the School of Veterinary Medicine, you will join the Section of Molecular Cellular Medicine within the Discipline of Comparative Biomedical Sciences. In the role you will: Establish and lead a sustainable research group, developing complex, multi-organ in vitro models for predictive disease research Work collaboratively with other researchers in the School to design and develop applications of in vitro models in their research areas Generate high quality publications and demonstrable impact Secure significant external research income to support the work of your research group Foster cross-disciplinary collaborations, including in silico modelling e.g. digital twins Enhance industry engagement and translational research impact. Mentor postgraduate research students and postdoctoral fellows Make high quality, research-led contributions to undergraduate and postgraduate teaching within the School, including on the RCVS-accredited BVMSci veterinary degree course. About you Our Senior Lecturers and Associate Professors play an important role in advancing research and innovation and influencing the future of the veterinary profession. As such, you will have: Proven track record in technology-driven in vitro model development. Evidence of real-world application of models across multiple research fields. Ability to contribute to 3Rs objectives in cancer, pain, vascular and gut research. A proven track record of substantial external research grant income generation A proven commitment to delivery of inspiring, engaging learning and teaching at undergraduate and postgraduate level Experience in silico modelling collaborations to enhance predictive power and a strong track record of cross-sector partnerships (academia, industry, regulatory bodies) are desirable. To apply When completing the online application form, we would welcome: a cover letter (no more than 2 pages), your CV and a brief supporting statement/ vision document (no more than 3 pages) outlining your intended five-year research plan. Informal enquiries can be made to Dr Martha Betson, Head of Department, Comparative Biomedical Sciences (m.betson@surrey.ac.uk) or Dr Giovanna Nalesso, Associate Head, Research and Innovation (g.nalesso@surrey.ac.uk). We wish to create the conditions for success for our new starters in the Vet School, by facilitating their growth and development within our institution. To achieve this, we have established the following guiding principle for all new staff members who are on a local/Guildford contract, effective for all new starters.  Four-Day On-Campus Commitment: New staff into this post are expected to be physically present on campus for a minimum of four days each week during their initial four to six months of employment. This requirement is adjusted on a pro-rata basis for part-time staff members. Further details Job Description Job Description

Research Assistant Health and Social Sciences Cluster Singapore Institute of Technology We are seeking a motivated and capable Research Assistant to join an exciting translational research project on spinal sarcopenia in older adults, with a focus on muscle degeneration, senescent progenitors, and regenerative failure. This role offers a unique opportunity to work across clinical research, functional assessment, imaging analysis, and laboratory investigation in a multidisciplinary academic environment. The successful candidate will support a funded research project that aims to generate clinically relevant insights into ageing, muscle health, and spine-related conditions. This is an excellent opportunity for candidates who are passionate about meaningful research and wish to build strong experience in applied human and translational studies. Key Responsibilities Support the Principal Investigator and research team in the implementation and coordination of the project Assist with participant recruitment, scheduling, follow-up, and study administration in accordance with approved ethics protocols Conduct and document functional assessments and study-related data collection Retrieve, organise, and manage imaging data, and assist with image-based analysis Support laboratory workflows such as tissue handling, histology, immunofluorescence, qPCR, ELISA, and related analyses Maintain accurate databases, study records, and project documentation Assist with literature review, data cleaning, preliminary analysis preparation, reporting, and regulatory submissions Coordinate procurement of reagents, consumables, and research-related items Ensure compliance with laboratory safety, biosafety, and institutional research governance requirements Job Requirements Bachelor’s degree in biomedical science, life sciences, physiotherapy, diagnostic radiography, medical laboratory science, or a related discipline Strong interest in translational, musculoskeletal, ageing, or clinical research Experience in clinical research coordination, patient-facing data collection, imaging analysis, or laboratory techniques will be advantageous Familiarity with histology, microscopy, immunofluorescence, molecular assays, or tissue-based workflows is preferred Good written and verbal communication skills Strong organisational skills, attention to detail, and professionalism Proficiency in Microsoft Office; familiarity with ImageJ, SPSS, STATA, or equivalent tools is an advantage Key Attributes Motivated, responsible, and able to work independently Careful and accurate in handling data, samples, and documentation Strong team player who can work effectively with academic, clinical, and student collaborators Willingness to learn and adapt in a dynamic multidisciplinary research environment Why Join Us This role offers valuable exposure to clinically relevant translational research with opportunities to develop experience in human studies, imaging, laboratory science, and multidisciplinary collaboration. The successful candidate will contribute to a meaningful project with real-world healthcare relevance while building a strong foundation for future research or postgraduate opportunities. Contract Type 1-year contract Work Location Singapore Institute of Technology, with project activities at SIT and partner sites as required.