Computational statistics and deep learning to strengthen families and reduce violence towards children University of Oxford in United Kingdom

Commercial partner: IDEMS International Community Interest Company: Innovations in Development, Education and the Mathematical SciencesAdditional partner: Parenting for Lifelong Health This studentship builds on a six-year-long collaboration between Oxford researchers and IDEMS International, including the recent successful randomized controlled field trial in Tanzania on a hybrid-digital parenting app to reduce violence towards children (Awah et al, 2021; Baerecke et al 2022).The student will develop computational statistical and deep learning methods to harness the power of digital tools to strengthen families and protect children. A central pillar of this work is that interventions be designed for low- and medium-resource global health settings (e.g., cheap mobile phones without constant internet access) and co-created with in-country experts so that local knowledge is embedded from day one.Three proposed projects will form chapters of the thesis:1) machine learning to automatically classify records of parent/child interactions (audio, video, or text) and recommend tailored parenting support. On-device processing power and upload bandwidth are both limited, meaning that new computational approaches (such as knowledge distillation, lowering precision, and layer reuse) will be necessary for low and medium-resource settings.2) using large language models (LLMs) to aid in the development stage of very large but deterministic offline parenting chatbots in multiple languages. Chatbot safety is of paramount importance, but we believe LLMs can play an important role in building out a very large set of questions and answers to be verified by experts before deployment.3) beyond "A/B testing": causal inference to understand heterogeneous treatment effects of parenting app design and content choices during deployment in the real world. Machine learning has contributed to an explosion of new methods for causal inference, including doubly robust methods and causal forests (Athey et al, 2019). Further developing these new approaches in quasi-experimental settings will lead to major advances in the external generalizability of controlled trials.Data availability: Data from the ParentApp randomised trial is already shared between the Universities of Oxford, Cape Town, Tanzania National Institute for Health Research, and IDEMS. This will be made available to the student and team working on this project. In addition, all users of the ParentApp program agree to the non-profit use of their data by the development and research team with the goal of improving the effectiveness of the program - again this will be available for the student and team to use.Ethical approval is underway, as amendments to broader ethical approvals for the development and testing of hybrid-digital approaches to delivery of parenting programs.Apply using course: DPhil in Computer ScienceMRC INDUSTRIAL CASE STUDENTSHIPS 2025Designed to nurture the academic entrepreneurs of the future, the Enterprise studentship programme offers a stimulating educational experience as part of the Oxford-MRC DTP cohort, with the additional benefit of working closely with an industrial partner. This will provide entrepreneurial training opportunities and an insight into how commercial science is conducted alongside a superb academic base within the University. Students will work for at least 3 months in the associated company.ELIGIBILITYThey are open to both UK and non-UK nationals and will follow the UKRI student eligibility requirements. UKRI will normally limit the proportion of international students appointed each year through individual training grants to 30% of the total intake each year.FUNDING PACKAGEEach iCASE studentship is fully-funded - it includes four years of stipend at the UKRI stipend level + £2,500 p.a., course fees, and a generous research training support grant.APPLICATIONS DEADLINEApplications must be received by 12 noon (UK time) Tuesday 3 December 2024. Details on entry requirements and how to apply can be found below.For details of entry requirements please go to the Oxford-MRC DTP iCASE 2025 Projects page.HOW TO APPLYBefore applying for this project we recommend you contact the lead supervisors for informal discussion.To make a formal application, please complete the University’s online application form for the DPhil course specified under the project description above. Please indicate the iCASE project clearly by inserting ‘iCASE’ before the project title and by using the reference code iCASE. You will need to provide a personal statement (500 words max if applying for a project hosted by one of Medical Sciences departments - please note that this limit might be different if a project is hosted by one of MPLS departments in which case follow their requirement) detailing your interest and fit for the studentship. Note that no project proposal is required for the iCASE studentship applications.If you wish to apply for a combination of iCASE and other projects within the hosting department, this can be done on the same application form (max number of projects you can apply for on one application depends on the department you wish to apply to). If you wish to apply for iCASE projects within different departments, you will have to make separate applications directly through those departments.If you have any queries about the iCASE application process (questions about the project should be directed to the lead supervisor), please email [email protected].