ZZ006612 - Research Fellow in Deep Learning Models for Medical Data
School of Computing

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Faculty of Technology

School of Computing

 

Research Fellow in Deep Learning Models for Medical Data

 

Employment type:  Fixed-term (to 30 March 2024)

Employment basis:  Full-time

Salary:  £35,845 - £39,152 per annum 

Post number:  ZZ006612

Date published:  15 January 2021

Closing date:  24 February 2021

 

Interview date:  03 March 2021

 

The University of Portsmouth is a dynamic and ambitious institution with a track record of success. One of only four universities in the south east of England to achieve a Gold rating in the Teaching Excellence Framework and ranked in the top 150 in the Times Higher Young University World Rankings.

 

This is an exciting opportunity to join an interdisciplinary research team to work full time, fixed-term (maximum 36 mths to the end of the project 30 March 2024), as a Research Fellow in Deep Learning at the School of Computing, University of Portsmouth. The successful applicant will undertake research on the EPSRC funded project (£762k) “Deep Learning Models for Fetal Monitoring and Decision Support in Labour”, which integrates with the research programme at the Oxford Centre for Fetal Monitoring Technologies, hosted at the Nuffield Department of Women’s and Reproductive Health, and the Big Data Institute, University of Oxford.

The Fellow will research, investigate, and apply innovative deep learning models for continuous automated evaluation of inputs as cardiotocography (CTG) signals during labour and others. The newly developed methods will be subsequently implemented on a hand-held device by the wider team.

The Fellow will be based at Portsmouth University, will have a Visiting Research Fellow status at Oxford University and will work closely with the entire multi-centre team.

The project outputs will contribute towards an automated clinical decision support tool at delivery wards to avoid asphyxia and brain injury of babies during childbirth.

Duties and Responsibilities

·         Work closely with the two Principal Investigators, based at Portsmouth and Oxford respectively, and support the multi-disciplinary research team, to deliver the relevant EPSRC-funded project objectives;

·         Research, investigate and apply novel Deep Learning Models for continuous risk assessment of the baby’s health during labour, utilising our unique maternity dataset comprising 100,000 births at term, provided by the Oxford Centre for Fetal Monitoring Technologies;

·         In particular, develop multimodal deep neural network (DNN) architectures, for both signal and image inputs, building on our preliminary Multimodal Convolutional Neural Networks (MCNN) models to allow the use of a variety of inputs: fetal heart rate; uterine contractions, spectrograms, clinical risk factors, etc. as independent learning branches in the overall architecture;

·         Support the implementation of the above algorithms into a software platform on a tablet (an App) to communicate with the clinicians and provide risk assessment, in conjunction with the team based at Oxford;

·         Take part in and support the testing, validation and assessment of the capability, accuracy, and efficiency of the models by conducting simulations and experiments with both real-time and retrospective data (including research visits at Oxford University).

Essential Criteria

·         A PhD* or equivalent professional qualification in Computer Science or Machine Learning, or equivalent research in relevant areas;

·         In-depth knowledge of machine learning methods and experience of applying deep learning approaches;

·         A background in data analytics, previous experience in computational modelling and using automated platforms for deep learning (Keras, PyTorch, or TensorFlow, etc.);

·         Critical thinking and problem-solving skills with attention to detail;

·         A collaborative approach to research and ability to work efficiently with diverse members of the team, as this role will integrate within a larger team across the collaborating Portsmouth and Oxford Universities;


Desirable Criteria

·         Experience working with healthcare data and/or clinical decision support software;

·         Drive and self-motivation to delivering research with real-world impact;

·         Aspirations for growth and development for new skills and expertise;

·         Good organisational, time-management, and priority-setting skills;


To explore the post further or for any queries you may have, please contact: Dr Ivan Jordanov, Reader, School of Computing, University of Portsmouth. Email: ivan.jordanov@port.ac.uk

*Applications from candidates who are working towards or nearing completion of a relevant PhD qualification will be also considered.

As an equal opportunities employer, we welcome applications from all suitably qualified persons and all appointments will be made on merit. As we are committed to the principles of the Race Equality Charter Mark, we would particularly welcome applications from the Black, Asian and Minority Ethnic (BAME) community who are currently under-represented at this level in this area.   

 

For detailed information about University of Portsmouth, please select this link: Working at Portsmouth

 

For detailed information about the vacancy, please select this link:  ZZ006612 - Researh Fellow in Deep Learning Models for Medical Data.docx

 

Vacancy Description
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Faculty of Technology

School of Computing

 

Research Fellow in Deep Learning Models for Medical Data

 

Employment type:  Fixed-term (to 30 March 2024)

Employment basis:  Full-time

Salary:  £35,845 - £39,152 per annum 

Post number:  ZZ006612

Date published:  15 January 2021

Closing date:  24 February 2021

 

Interview date:  03 March 2021

 

The University of Portsmouth is a dynamic and ambitious institution with a track record of success. One of only four universities in the south east of England to achieve a Gold rating in the Teaching Excellence Framework and ranked in the top 150 in the Times Higher Young University World Rankings.

 

This is an exciting opportunity to join an interdisciplinary research team to work full time, fixed-term (maximum 36 mths to the end of the project 30 March 2024), as a Research Fellow in Deep Learning at the School of Computing, University of Portsmouth. The successful applicant will undertake research on the EPSRC funded project (£762k) “Deep Learning Models for Fetal Monitoring and Decision Support in Labour”, which integrates with the research programme at the Oxford Centre for Fetal Monitoring Technologies, hosted at the Nuffield Department of Women’s and Reproductive Health, and the Big Data Institute, University of Oxford.

The Fellow will research, investigate, and apply innovative deep learning models for continuous automated evaluation of inputs as cardiotocography (CTG) signals during labour and others. The newly developed methods will be subsequently implemented on a hand-held device by the wider team.

The Fellow will be based at Portsmouth University, will have a Visiting Research Fellow status at Oxford University and will work closely with the entire multi-centre team.

The project outputs will contribute towards an automated clinical decision support tool at delivery wards to avoid asphyxia and brain injury of babies during childbirth.

Duties and Responsibilities

·         Work closely with the two Principal Investigators, based at Portsmouth and Oxford respectively, and support the multi-disciplinary research team, to deliver the relevant EPSRC-funded project objectives;

·         Research, investigate and apply novel Deep Learning Models for continuous risk assessment of the baby’s health during labour, utilising our unique maternity dataset comprising 100,000 births at term, provided by the Oxford Centre for Fetal Monitoring Technologies;

·         In particular, develop multimodal deep neural network (DNN) architectures, for both signal and image inputs, building on our preliminary Multimodal Convolutional Neural Networks (MCNN) models to allow the use of a variety of inputs: fetal heart rate; uterine contractions, spectrograms, clinical risk factors, etc. as independent learning branches in the overall architecture;

·         Support the implementation of the above algorithms into a software platform on a tablet (an App) to communicate with the clinicians and provide risk assessment, in conjunction with the team based at Oxford;

·         Take part in and support the testing, validation and assessment of the capability, accuracy, and efficiency of the models by conducting simulations and experiments with both real-time and retrospective data (including research visits at Oxford University).

Essential Criteria

·         A PhD* or equivalent professional qualification in Computer Science or Machine Learning, or equivalent research in relevant areas;

·         In-depth knowledge of machine learning methods and experience of applying deep learning approaches;

·         A background in data analytics, previous experience in computational modelling and using automated platforms for deep learning (Keras, PyTorch, or TensorFlow, etc.);

·         Critical thinking and problem-solving skills with attention to detail;

·         A collaborative approach to research and ability to work efficiently with diverse members of the team, as this role will integrate within a larger team across the collaborating Portsmouth and Oxford Universities;


Desirable Criteria

·         Experience working with healthcare data and/or clinical decision support software;

·         Drive and self-motivation to delivering research with real-world impact;

·         Aspirations for growth and development for new skills and expertise;

·         Good organisational, time-management, and priority-setting skills;


To explore the post further or for any queries you may have, please contact: Dr Ivan Jordanov, Reader, School of Computing, University of Portsmouth. Email: ivan.jordanov@port.ac.uk

*Applications from candidates who are working towards or nearing completion of a relevant PhD qualification will be also considered.

As an equal opportunities employer, we welcome applications from all suitably qualified persons and all appointments will be made on merit. As we are committed to the principles of the Race Equality Charter Mark, we would particularly welcome applications from the Black, Asian and Minority Ethnic (BAME) community who are currently under-represented at this level in this area.   

 

For detailed information about University of Portsmouth, please select this link: Working at Portsmouth

 

For detailed information about the vacancy, please select this link:  ZZ006612 - Researh Fellow in Deep Learning Models for Medical Data.docx