The Centre is currently advertising the following positions:

The Centre is currently advertising the following positions:

CRUK/EPSRC PhD Studentship in Network Cancer Medicine

EPSRC Centre for Mathematics of Precision Healthcare Joint PhD studentships

The EPSRC Centre for Mathematics of Precision Healthcare was set up at the end of 2016 and acts as an interface between mathematicians and computational data scientists with clinicians, basic medical scientists and healthcare economists in order to develop novel mathematical techniques to answer key questions in data-rich aspects of healthcare.

A huge amount of detailed healthcare data is becoming available as part of the trend towards data analytics and increasingly personalised patient care, from imaging and ‘omics characterization of disease, to social and economic aspects of public health. to the use of machine learning techniques for patient trajectories or for the analysis of free text in health records. There is huge potential in using this trove of information to help decision making in medicine and healthcare, both at the individual and population levels.

The EPSRC CMPH has a number of PhD studentships available starting in October 2018, where the successful candidates will join a centre of leading PhD students, postdocs and academics across departments at Imperial to develop the mathematical and algorithmic foundations around Machine learning, Data Science, Inference and Optimization, Network Science, and Artificial Intelligence in healthcare and medicine to help unlock this information. 

You should have an excellent academic record and passion for applied mathematics and modern computational and statistical methods.

We seek students that are open-minded, creative and willing to explore new ideas as part of a multidisciplinary team but at the same time committed to developing methods that are generic and transferable. The candidate should have excellent mathematical and computational skills, as well as outstanding presentation skills for various audiences. It is expected that candidates hold (or be near completion of) a top undergraduate degree in mathematics, physics, computer science, engineering, or equivalent quantitative backgrounds. The PhD positions will be based in the Department of Mathematics but will be highly collaborative.

Below we summarise three PhD projects that are currently available but the Centre is expected to appoint/host several additional PhD students in the broad areas described above. The positions only cover UK/EU fees.

To apply and for enquires please contact Dr Chloe Stockford (chloe.stockfor@imperial.ac.uk) and Prof Mauricio Barahona (m.barahona@imperial.ac.uk).

Applications should include a CV and names of two referees.

EPSRC Centre of Precision Healthcare joint with Cancer Research UK PhD Studentship in Network Cancer Medicine

Title: "Tracking the metabolic footprints of cancer using network analysis"

We have an exciting opportunity for a student who wishes to work at the interface of cancer biology, network theory and data science. The project is part of a thriving collaboration between the Biomathematics Group (D Oyarzún, M Barahona) and the Cancer Metabolism & Systems Toxicology Group (H Keun) at Imperial College London. The student will be based at EPSRC Centre for Mathematics of Precision Healthcare in South Kensington, at the heart of London's cultural and scientific quarter.

Description - Abnormal metabolism is a hallmark of cancer cells. Yet the complex connectivity of metabolic networks makes it difficult to establish how misregulation of specific pathways translates into malignant phenotypes. In this project we will study metabolism of tumour cells with a mix of network theory and high-dimensional data analysis. We will build graph models from genome-scale metabolic reconstructions and interrogate them with the various tools from network science, such as centrality analyses, graph embeddings and community detection.

The goal is to capture systemic changes in metabolic network for various environmental conditions and genetic alterations, so as to find new drug targets and biomarkers for tumour malignancy. Models will be refined with available omics datasets, together with cutting-edge metabolomics/fluxomics data from the Keun lab at the Department of Surgery & Cancer. We will test the novel therapeutic interventions with various interference experiments (siRNA, shRNA/CRISPR, small molecule inhibitors) in specific tumour cell models.

This is a well funded 4-year position for UK or EU nationals, co-funded by the Imperial College Cancer Research UK Centre and the EPSRC Centre for Mathematics of Precision Healthcare. The student will benefit from the thriving environment of the CMPH composed of mathematicians, clinicians and public health specialists working on data-based solutions for healthcare. This will also afford the student close contact with end users and industrial partners developing personalised cancer diagnostics and therapeutics. Experience with cancer biology and/or flux balance analysis would be advantageous.

EPSRC Centre of Precision Healthcare joint with Institute of Global Health Innovation PhD studentship

This PhD project is a collaboration between CMPH and the Institute of Global Health Innovation (IGHI). IGHI provides an extensive platform for collaborations with healthcare institutions, practitioners and medics within Imperial, the NHS and international partners. The Institute covers a broad spectrum of areas from organizational aspects of healthcare provision (patient safety, patient flows in hospitals, patient-sharing networks, socio-economic aspects of health provision, social media in healthcare) to areas of the adoption of innovation in healthcare to decision-making in public health and healthcare provision.

This project will focus on developing mathematical and computational frameworks for patient safety, patient flows, innovation adoption, social media and decision-making, utilizing big data in healthcare. The techniques are diverse but will likely include graphs, stochastic processes, machine learning, inference and optimization.

This project will be funded for 3.5 years and is open to UK/ EU nationals.

EPSRC Centre of Precision Healthcare joint with Medical Research Council Doctoral  Training Council PhD Studentship

This is an open-ended project to be developed in collaboration with the MRC DTP (Medical Research Council Doctoral Training Partnership).  The project will focus on mathematical and computational techniques in the general areas of medical research from modelling to data integration, imaging, modelling of infectious disease, early and enhanced discovery in disease, patient stratification, social aspects of disease, or personalisation of therapy.

The student will be based in the Department of Mathematics and the EPSRC CMPH but will also be integral part of the MRC DTP cohort, thus allowing for the integration with a multidisciplinary group of students.

This project will be funded for 3.5 years and is open to UK/EU nationals that fulfill the UK residency requirement (3 years in the UK).

Enterprise DTP: MRC iCASE Doctoral Training Programme

Enterprise DTP: MRC iCASE Doctoral Training Programme

PhD project: Adolescent mental health and cognitive development in the SCAMP cohort: investigating multifactorial pathways to better understand the development of mental health resilience and vulnerability during adolescence.

Project description:

One in six 15-19 year-olds in the UK show symptoms of mental illness, with half of adult mental illness manifesting during adolescence, a time of mental vulnerability. Importantly, the reasons for this are not well understood. SCAMP is a prospective adolescent cohort study (current average age 15), established to investigate whether digital social environments are associated with cognitive, behavioral, educational, physical and mental health outcomes during adolescence. SCAMP participants are representative of the general school population across London in terms of age, gender, socio-economic status and ethnicity.

The SCAMP study has collected a rich array of data on social, educational, hormonal, environmental and lifestyle risk factors on mental and physical health during adolescence. The principal aim of this studentship is to investigate specific scientific questions such as: (A) to examine the relationships between adolescent’s digital social environments and mental health, including the interplay with physical health, physical activity, sleep and adiposity; and (B) to examine the complex inter-relationships between pubertal hormone profiles, and cognitive factors such as cognitive control, emotional reactivity and mentalising, to further our understanding of both mental health resilience and vulnerability during adolescence. Given that peer relationships in digital social environments, together with other factors, are critical to the developing adolescent brain, this is an exciting opportunity to undertake analysis investigating multifactorial pathways to better understand the development of mental health resilience and vulnerability during adolescence. Within this project, there is scope for the student to focus in on the aspects of most interest to them. 

About the studentship:

This project is supported by the Enterprise DTP iCASE programme and is based at the Department of Epidemiology and Biostatistics at Imperial College London, in collaboration with the commercial partner Delosis Limited. The studentship is fully supported for 3.5 years, and includes payment of fees at UK/EU rate and other project costs, as well as a tax free stipend of at least £18,000 per annum. As a CASE project, the student will spend at least one month a year with Delosis, allowing them to obtain a unique experience of a commercial, research technology environment. 

Additionally, the student will also benefit from the support of the Imperial College MRC Supplement scheme, which provides MRC students with the opportunity to apply for funding to support their PhD studies, in areas such as high end training, internships and post PhD transition. 

The student will also benefit from being part of the Imperial College MRC DTP, one of the largest and most established DTPs at Imperial College, and is led by the Director, Professor Laki Buluwela.

The academic environment

The project will be supervised by Professor Mireille B Toledano, Professor in Perinatal & Paediatric Epidemiology, Imperial College London, who leads an excellent multi-disciplinary supervisory team, that interfaces across epidemiology, database programming, geographical information systems, and statistical methodology. The project will form part of the research programme of the national MRC-PHE Centre for Environment and Health - an international centre of excellence for research and training on the health effects of environmental pollutants and the translation of this knowledge to inform national and international policies to improve health.

Eligibility:

Applications are invited from candidates who hold a Masters supported by a first degree, or a first degree only, based in areas aligned to the project (e.g. public health, psychology, environmental science, mathematics, statistics, medical statistics, etc). Enterprise DTP Studentship eligibility can be found on the programme web page.  

How to apply:

To apply for this studentship, please complete the online DTP studentship application form, which will be live until the  (4th January 2019, 23.59 GMT). Before you begin, please prepare your personal statement and have access to details of your qualifications and achievements, as progress on the online form cannot be saved. 

Informal discussions prior to application with Professor Mireille B Toledano (m.toledano@imperial.ac.uk) are welcome.

 

PDRA in Single Cell Stochastics and Inference

PDRA in Single Cell Stochastics and Inference: Ageing and Mitochondrial Transcriptomics 

Closing date 15 April 2019

Applications are invited for a 2-year PostDoc joint between the labs of Nick Jones (Imperial Maths) and Patrick Chinnery (Cambridge Mitochondrial Biology Unit/Clinical Neuroscience) merging single cell stochastics, statistics and omics to study mitochondrial ageing.

This project joins three timely themes: ageing; single-cell sequence data and mitochondria (cellular power stations). Each of our cells can contain thousands of mitochondria each with their own genomes (mitochondrial DNA, mtDNA). Mutations in mtDNA have been implicated in numerous conditions of ageing (from neurodegeneration to cancer) but until now we have had limited means to associate the, possibly mutated, mtDNA sequences in individual cells with the cellular state of those cells (as indicated by transcriptome or other data). This appointment will help bridge the gap between the genetic state of cellular power stations and the state of the aged cell. By these means we can help elucidate a key question in the field: the role of mtDNA mutation in ageing. The researcher will statistically link stochastic models for mtDNA evolution to single-cell mtDNA and RNA sequencing data. A background in biology or bioinformatics is not required and candidates might have backgrounds in statistics, statistical genetics, statistical physics, applied mathematics or related disciplines. Some experience with data manipulation and substantial experience with programming is required. The appointee will join the Centre for the Mathematics of Precision Healthcare, the Cambridge Mitochondrial Biology unit and a new subgrouping in Imperial Mathematics on Single Cell theory and data.

We welcome candidates from all backgrounds and value a supportive environment prioritizing purposeful happiness. 

https://www.imperial.ac.uk/jobs/description/NAT00413/research-associate 

Relevant links:
http://systems-signals.blogspot.com/
https://www.imperial.ac.uk/people/nick.jones/
http://www.mrc-mbu.cam.ac.uk/people/patrick-chinnery
http://www.imperial.ac.uk/mathematics-precision-healthcare/  
 

 

PhD studenship in machine learning methods for controlling antibiotic resistance

EPSRC Centre for Mathematics of Precision Healthcare Joint PhD studentships

Title: Analysis and Prediction of Carbapenem-Resistance in Healthcare-Associated Infections

We have an exciting opportunity to develop next-generation machine learning methods for controlling antibiotic resistance, the most pressing challenge in global health. The project is part of a thriving collaboration between the EPSRC Centre for Mathematics of Precision Healthcare (CMPH, Dept. Mathematics) and the Health Protection Research Unit in Healthcare-associated Infections and Antimicrobial Resistance (HPRU, Dept. Medicine) at Imperial College London. 

Description: The student will develop cutting-edge tools to forecast and control the prevalence of carbapenem- resistance, a particularly critical type of resistance. They will employ time-series analysis and machine learning to time-resolved data from the Imperial College Healthcare NHS Trust, working closely with the Trust’s Epidemiology team, to quantitatively predict and optimise the impact of interventions. They will learn advanced quantitative skills in health data science and join a cross- disciplinary ecosystem of mathematicians, clinicians and public health specialists. The ideal candidate should have an excellent academic record and excellent mathematical and computational skills. 

This is a 4-year position for UK and EU nationals who fulfill the usual 3-year UK residency requirements. It is co-funded by the CMPH and the Medical Research Foundation. The student will benefit from the thriving environment of the CMPH and HPRU composed of mathematicians, clinicians and public health specialists working on data-based solutions for healthcare. This will also afford the student close contact with end users and industrial partners, and as part of the Medical Research Foundation National PhD Training Programme in Antimicrobial Resistance Research, they will have enhanced training opportunities. 

Application process: Applicants should send a full CV (including the names and email addresses of at least two academic referees), and personal statement (detailing why they are interested in the research project) to Dr Andrea Weisse (andrea.weisse@imperial.ac.uk). Suitable candidates will be then asked to complete an electronic application form at Imperial College London in order for their qualifications and eligibility to be assessed by College Registry.

Application deadline: 31 March 2019

 

Please contact Anna Radomska with any informal enquiries.