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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
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.
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.
EPSRC funded PhD position
Job Description:
The human skin microbiome plays a critical role in maintaining skin health. For example, skin microbiota speeds up skin regeneration and repair of acute wounds. Skin healing after micro-wounding varies between body sites – specifically two notable locations where healing rates vary are the skin on the face and the skin on the neck. While healing is faster on the neck, shaving this location also results in more ingrown hairs than the face. Ingrown hairs are problematic because they elicit inflammation and cause bumps, which razor blades can cut upon the next shave, creating an ongoing cycle of skin damage and irritation. This MRes + PhD project aims to understand the skin microbiome's roles in healing micro-wounds on the face and neck and propose solutions that leverage the skin microbiome to enhance skin healing to address shave-induced nicks and cuts. We will take an interdisciplinary approach first developing computational models that describe an intricate dynamic interplay between skin microbes and cells, then subsequently we will experimentally evaluate model predictions in vitro. Specifically, we will first develop a computational model of stable communities of dominant microbes from healthy skin that describes the dynamic interactions between skin microbes and cells, considering the effects of environmental factors (pH, humidity, immune response and nutrients). These computational models will be based on metabolomics and microbiome profiling data that will be collected by the student, from hair follicles on the face and neck at the start of the PhD. We will use the mathematical model to decide how the skin microbiome and environmental factors impact micro-wounds healing processes by evaluating the intrinsic healing properties of epithelial cells isolated from hair follicles on the face and neck. This research will allow us to devise therapeutic strategies to mitigate or augment both micro-wounds healing and trapped hairs after shaving. This project is highly multi-disciplinary to create multi-scale understanding of the role of skin microbiome in wound healing process. The ideal student for this project will have experience in conducting systems biology projects and developing computational models of biological systems with a keen interest in learning skin microbiome biology. A strong computational and mathematical background is required. There will be a broad range of training available across many bioengineering skills, including the opportunity to work in vivo and in vitro, and many networking opportunities given the supervisory team spans the Imperial College London, P&G Reading Innovation Centre, and Northumbria University. Apply for a studentship via the link below to join the EPSRC CDT in Chemical Biology: Empowering UK BioTech Innovation. Deadline: 3 June 2024
Title:
A systems biology approach to understand the role of skin microbiome in healing of micro-wounds on the face and neck