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Prospective PhD students are strongly encouraged to apply for an Imperial College PhD studentship. Alternatively, there are other competitive studentships.
Academic visitors are also welcome.
If you are interested in any of the above, please email your CV and research statement to Dr Reiko Tanaka (r.tanaka@imperial.ac.uk).
Current Vacancies
Leverhulme Trust-funded PhD position
Job Description:
Join the Tanaka group as a PhD student and be a part of the Centre for Holobiont Research. Holobiont is a term that refers to a larger organism, such as animal, plant or fungus, together with its associated community of microbes and is an underexplored area of research and innovation. The PhD student will be funded by the Leverhulme Trust and will research and develop computational/mathematical frameworks to identify minimal systematic relationships and interaction network structures that define “healthy” functioning vs disrupted microbiome-host relationships in holobionts. The PhD student will apply a mathematical modelling approach to develop an in silico framework to model and simulate microbiome dynamics, and generate in silico microbiomes of different hosts by fitting the in silico model to data of microbiome fractions from Centre for Holobiont Research members on e.g. human skin, frog skin, fruit skin, plant roots, bee guts. This will enable us to identify key design principles (microbiome interaction network features/motifs) of stable and robust holobionts, to make the microbiome more robust to disturbances. The PhD student will work on this novel project and use state-of-the-art mathematical/computational modelling and machine learning techniques in a collaborative working environment. Applicants should have excellent mathematical skills, programming expertise, and experience in mechanistic modelling of biological systems. They should have a Masters in computational systems biology, applied mathematics, or a closely related discipline, with previous experience in statistical and machine learning methods and knowledge in basic biology. The candidate should have excellent interpersonal, written and oral communication skills and enthusiasm for exposure to a diversity of scientific projects. They should be able to work independently and as part of a team. We offer a very supportive and stimulating work environment. We encourage application from talented and ambitious research students with a passion for scientific discovery and a desire to make a difference in society. The PhD student will join a friendly and inclusive team that champions diversity and prioritises the career growth of its researchers. Deadline: 11 February 2025
Research Area:
Holobiont Computational Systems Biology
EPSRC-funded PhD position
Research Area:
Computational Biology: Unveiling Skin pH Regulation Mechanisms
Job Description:
Are you passionate about using computational approaches to solve complex biological challenges? Join the Tanaka Group at Imperial College London as a PhD student and play a pivotal role in advancing our understanding of skin pH regulation through computational modelling. This exciting PhD project, supported by Procter & Gamble and funded by the EPSRC Industry Doctoral Landscape Awards (IDLA), offers a unique opportunity to work at the intersection of academic research and industry innovation. The project is expected to start in October 2025. The funding will cover stipend and home fees for 4 years. There is a possibility to accept international students. PROJECT OVERVIEW Skin barrier homeostasis emerges from a delicate interplay between cellular processes such as proliferation, differentiation, enzymatic activity, and the influence of the skin microbiome—all of which are regulated by pH. In this project, you will develop a biology-based computational model to uncover the mechanisms of pH regulation in human epidermal tissue. Your work will focus on: - Exploring the dynamics of skin barrier homeostasis. - Simulating the epidermis’ responses to consumer-relevant perturbations, such as occlusion or microbial colonization. - Identifying novel strategies to promote and maintain healthy skin under challenging conditions. This project will provide you with the opportunity to delve into the rich complexity of human biology while applying cutting-edge computational approaches. The insights gained will have real-world implications, shaping innovative interventions for skin health and beyond. WHO SHOULD APPLY? We’re looking for motivated and talented individuals with: - Strong mathematical and programming skills and experience in mechanistic modelling of biological systems. - A Master’s degree in computational systems biology, applied mathematics, or a closely related field. - A basic understanding of biology. - Excellent interpersonal, written, and oral communication skills. A collaborative spirit, alongside the ability to work independently and contribute to a team. WHY JOIN US? At the Tanaka Group, you’ll find a supportive, inclusive, and stimulating research environment where your growth and success are our priorities. By joining our team, you’ll benefit from: - Working on a cutting-edge, interdisciplinary project with direct industry relevance. - A friendly and diverse team that values open scientific discussions and creative thinking. - A chance to make a tangible impact on society by addressing real-world challenges in skin health. - Opportunities for collaboration with world-leading researchers at Imperial College London. If you’re ready to embark on a journey of discovery and innovation, we’d love to hear from you. Apply today and become part of a team dedicated to pushing the boundaries of computational biology and making a difference in people’s lives. HOW TO APPLY Please email Professor Reiko Tanaka (r.tanaka@imperial.ac.uk) your CV and personal statement. The application will be considered on a rolling basis.
Research Assistant or Associate
Job Description:
Teledermatology is fast becoming the norm. The Tanaka group at Imperial College London has developed a new deep-learning pipeline called EczemaNet (Pan, Hurault et al. 2020) that can perform eczema severity assessment fully automatically and in a reliable and interoperable fashion. Eczema is a chronic inflammatory skin condition that affects millions of people worldwide. Eczema severity assessment is critical for deciding which treatments are needed and if specialist referral is required. However, judging eczema severity on 2D images can be challenging, subjective, and prone to inter- and intra-observer variation. EczemaNet has been developed to address these challenges. DUTIES & RESPONSIBILITIES We are excited to offer an opportunity for a research assistant/associate to join our dynamic team to develop the user-interface for EczemaNet. This role is programming and data-science intensive. The main responsibilities of this post will include design, development, and maintenance of both the front-end and back-end of the EczemaNet user-interface that will be used by clinicians, nurses, and general public. The research assistant/associate will plan, lead, and carry out a high-quality implementation of the AI tool to develop a regulatory-compliant medical device. ESSENTIAL REQUIREMENTS We look for highly motivated applicants with excellent interpersonal and technical skills, enthusiasm for development of quality user-interface for clinical use, and great attentions to details. Please provide your GitHub or equivalent profile (e.g. descriptions of previous projects) in the application.
MRC-funded PhD Position
Research Area:
Mechanistic and interpretable AI
Job Description:
Are you passionate about developing AI methods to solve real-world healthcare challenges? Join Imperial College London as a PhD student and contribute to advancing personalised, interpretable forecasting of eczema severity. This exciting PhD project focuses on building next-generation AI tools that move beyond black-box prediction, combining mechanistic understanding with modern machine learning. The project offers a unique opportunity to work at the intersection of artificial intelligence, dermatology, and systems biology. Project Overview: Eczema affects millions worldwide with unpredictable flare-ups that are difficult to manage. Currently, patients react after symptoms appear. This project will develop AI tools that predict flares, enabling proactive treatment. We will create a personalised forecasting system using smartphone photos, skin barrier measurements, and biological markers (bacteria, lipids). Unlike "black-box" AI, our system explains predictions, e.g. "elevated flare risk due to rising bacteria in infection-sensitive skin". This mechanistic interpretability builds trust and helps patients understand their disease. Using unique data from 11 patients tracked over three months (photos, barrier measurements, bacterial samples), the student will develop AI models that learn individual disease patterns and predict severity changes 1-3 days ahead. This interdisciplinary project bridges AI, dermatology, and systems biology. Skills training includes • Machine learning (Bayesian modelling, time-series forecasting, computer vision) • Statistical analysis of biomedical data • Clinical and industry collaboration • Scientific communication • Software development Objectives: Year 1: Integrate image-based severity assessment with forecasting Year 2: Incorporate barrier measurements; develop mechanistic interpretability Year 3: Generate personalized treatment recommendations; plan for larger validation studies Who should apply? We are looking for motivated and talented individuals with: • Strong background in machine learning, applied mathematics, or a related field • Experience in time-series modelling, probabilistic methods, or deep learning • Interest in interpretable or mechanistic AI approaches • Programming skills (e.g. Python, PyTorch/JAX) • An interest in healthcare or biomedical applications • Excellent communication skills and ability to work in an interdisciplinary team Why join us ? By joining this project, you will benefit from: •Working on a cutting-edge problem at the interface of AI and healthcare • Developing methods that combine predictive performance with interpretability • Access to unique longitudinal, multimodal biomedical data • A collaborative environment involving clinicians, biologists, and data scientists • The opportunity to contribute to tools with direct clinical and societal impact If you are interested in building interpretable AI systems that can directly improve patient care, we encourage you to apply and be part of this interdisciplinary effort. Applications will be considered on a rolling basis.
Research Assistant or Associate
Job Description:
The Tanaka group at Imperial College London is seeking a highly motivated and skilled Research Assistant/Associate to join our team on an exciting project aimed at developing a bespoke remote monitoring technology that can provide early warning of asthma attacks. Your role involves conducting data-driven analysis of clinical data on longitudinal lung function, time series data analysis to detect early warning signals of critical transitions, and mechanistic modelling to connect potential causes of airway obstruction to the short-term longitudinal pattern of lung function. DUTIES & RESPONSIBILITIES As a Research Assistant/Associate, you will have the opportunity to work with a team of enthusiastic researchers including mathematicians, computational biologists, experimentalists, and clinicians. You will plan, lead and carry out a high-quality research program in systems medicine, focusing on mechanistic modelling and machine learning analysis of clinical and experimental data. Your work will have a direct impact on the lives of patients suffering from asthma and fill the significant unmet healthcare need to prevent wheeze attacks in preschool children. This is an excellent opportunity to be a part of a dynamic team, in close collaboration with Professor Sejal Saglani (NHLI, Imperial College London). We offer a supportive and stimulating work environment. If you are a talented and ambitious researcher with a passion for scientific discovery and a desire to make a difference in society, we encourage you to apply for this exciting opportunity. ESSENTIAL REQUIREMENTS The successful candidate will have excellent analytical skills, programming expertise, and experience in machine learning and mechanistic modelling. They should have a PhD or Masters degree in systems biology, applied mathematics, or a closely related discipline, with previous experience in statistical and machine learning methods and knowledge in basic biology. The candidate should have excellent interpersonal, written and oral communication skills and enthusiasm for exposure to a diversity of scientific projects. They should be able to work independently and as part of a team. Experience in working with clinical datasets and knowledge of asthma pathophysiology will be advantageous.
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