Research Associate in Bioengineering Imperial College School of Bioengineering United Kingdom

Job Title:Research Associate

Reference: ENG00884
Date posted: 21 June 2019
Closing date: 22 July 2019
Key information about the role
Location:South Kensington Campus
(map)
Position type:Full time, fixed term
Salary:£37,486 – £40,858 plus benefits

 

 

Job summary


Imperial College London is a science-based institution with the greatest concentration of high-impact research of any major UK university. All of our academic departments are located on a single campus in South Kensington, giving a concentration of talent that creates a stimulating and vibrant research community. You can find out more about our staff benefits, including generous annual leave entitlements and our excellent professional...


Job summary


Imperial College London is a science-based institution with the greatest concentration of high-impact research of any major UK university. All of our academic departments are located on a single campus in South Kensington, giving a concentration of talent that creates a stimulating and vibrant research community. You can find out more about our staff benefits, including generous annual leave entitlements and our excellent professional development opportunities, here: http://www.imperial.ac.uk/job-applicants/staff-benefits/.

 

Department

 

The Department of Bioengineering at Imperial College London is leading the bioengineering agenda both nationally and internationally, advancing the frontiers of our knowledge in the discipline's three main areas: Biomedical Engineering (Developing devices, techniques and interventions for human health), Biological Engineering (Solving problems related to the life sciences and their applications for health), Biomimetics (Using the structures and functions of living organisms as models for the design and engineering of materials and machines). Royal School of Mines and its adjacent Bessemer buildings, the Department boasts state-of-the-art laboratories, including 'wet labs' for cell culture, chemistry, histology, flow studies, biosensors and electrophysiology, biomaterials, molecular biology, and high throughput biological screening; as well as 'dry labs' for modelling, electronics, imaging and mechanics. The space has been designed to promote greater interaction among researchers – just what is needed for the interdisciplinary field that is modern bioengineering.

 

Duties and responsibilities


The role of the person appointed with this position will be the establishment of activities within neural signal processing, specifically in relation to the European Research Council (ERC) synergy grant NaturalBionicS. This implies expertise in signal processing, parallel computation, machine learning, and experimental skills for intramuscular and surface EMG recordings.

 

Essential requirements


The post is funded by the European Research Council Synergy Grant Natural BionicS and aims at translation research in motor neuroscience within the application areas of upper limb prosthetics. This position specifically refers to the signal processing activities in the project.

To carry out research in signal deconvolution, blind source separation, and real-time processing, specifically in relation to spike sorting of motor neuron activity, with the translational aim of identifying new control approaches for upper limb prostheses. In addition, the Research Associate will be expected to submit publications to refereed journals and to attract external research funding.

 

You will have:


• PhD (or equivalent) in Bioengineering, Electronics Engineering, Human Medical Sciences or a closely related discipline.
• At Research Assistant level: a good undergraduate degree or MSc ( or their equivalents) in mathematics, physics or engineering; candidates with demonstrable experience in data science will be considered
• Knowledge of myoelectric control systems and non-invasive neural interfacing
• Knowledge of physiological model of EMG signal generation
• Knowledge of EMG signals acquisition; Experience in intramuscular EMG signal acquisition
• Deep knowledge on EMG signal decomposition techniques, including intramuscular and surface EMG signal decomposition, specifically pattern recognition methods (knowledge of machine learning), blind source separation algorithms, off-line and on-line methods
• Knowledge of probability theory and statistical signal processing
• Knowledge of parallel computation, especially GPGPU computation (General-purpose computing on graphics processing units)
• Experience in non-invasive motor neuron activity recordings and analysis
• Ability to conduct a detailed review of recent literature
• Ability to develop and apply new concepts
• Creative approach to problem-solving
• Excellent verbal communication skills and the ability to deal with a wide range of people
• Excellent written communication skills and the ability to write clearly and succinctly for publication
• Ability to direct the work of a small research team and motivate others to produce a high standard of work
• Ability to organise own work with minimal supervision
• Ability to prioritise own work in response to deadlines
• Advanced computer skills, including word-processing, spreadsheets and the Internet
• Flexible attitude towards work
• Discipline and regard for confidentiality and security at all times

 

You will be:


• Computer literate with a good knowledge of different computer programs, especially in Matlab and CUDA C++, with experience in neurophysiological signal decomposition
• Willing to work as part of a team and to be open-minded and cooperative
• Willing to undertake any necessary training for the role

Further information
You must have a good undergraduate degree/ MSc in Biomedical Engineering (or equivalent) and a PhD in Biomedical Engineering, or Electronics Engineering, or Human Medical Sciences (or equivalent) for appointment at Research Associate level.

You will have previous experience in myoelectric signals, neural interfacing, myoelectric algorithm development, probability theory and statistical signal processing, parallel computing.

*Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant within the salary range £34,397 - £35,910 per annum.

For informal enquiries about the post please contact Professor Dario Farina at d.farina@imperial.ac.uk

Our preferred method of application is online via our website. Please click 'apply' below or go to https://www.imperial.ac.uk/job-applicants/ (Select "Job Search" then enter the job title or vacancy reference number into "Keywords"). Please complete and upload an application form as directed quoting reference number ENG00xxx. Further information is also available on the job description.

Any queries regarding the application process should be directed to Miss Jo Adam at i.adam@imperial.ac.uk

Closing Date: 4 weeks from the date of posting

 

Imperial Managers lead by example.


Committed to equality and valuing diversity. We are also an Athena SWAN Silver Award winner, a Stonewall Diversity Champion, a Two Ticks Employer, and are working in partnership with GIRES to promote respect for trans people

The College is a proud signatory to the San-Francisco Declaration on Research Assessment (DORA), which means that in hiring and promotion decisions, we evaluate applicants on the quality of their work, not the journal impact factor where it is published. For more information, see https://www.imperial.ac.uk/research-and-innovation/about-imperial-research/research-evaluation/

 

About us


The College believes that the use of animals in research is vital to improve human and animal health and welfare. Animals may only be used in research programmes where their use is shown to be necessary for developing new treatments and making medical advances. Imperial is committed to ensuring that, in cases where this research is deemed essential, all animals in the College's care are treated with full respect, and that all staff involved with this work show due consideration at every level. http://www.imperial.ac.uk/research-and-innovation/about-imperial-research/research-integrity/animal-research/

 

Documents


Research Associate job description person specification_.pdf
About Imperial College London
Imperial College London is the UK's only university focussed entirely on science, engineering, medicine and business and we are consistently rated in the top 10 universities in the world.

You will find our main London campus in South Kensington, with our hospital campuses located nearby in West and North London. We also have Silwood Park in Berkshire and state-of-the-art facilities in development at our major new campus in White City.

We work in a multidisciplinary and diverse community for education, research, translation and commercialisation, harnessing science and innovation to tackle the big global challenges our complex world faces.

It's our mission to achieve enduring excellence in all that we do for the benefit of society – and we are looking for the most talented people to help us get there.

 

Additional information


Please note that job descriptions cannot be exhaustive and the post-holder may be required to undertake other duties, which are broadly in line with the above key responsibilities.

 

All Imperial employees are expected to follow the 7 principles of Imperial Expectations:

 

Champion a positive approach to change and opportunity
Communicate regularly and effectively within, and across, teams
Consider the thoughts and expectations of others
Deliver positive outcomes
Encourage inclusive participation and eliminate discrimination
Develop and grow skills and expertise
Work in a planned and managed way
In addition to the above, employees are required to observe and comply with all College policies and regulations.

Imperial College is committed to equality of opportunity, to eliminating discrimination and to creating an inclusive working environment. We are an Athena SWAN Silver award winner, a Stonewall Diversity Champion, a Disability Confident Employer and work in partnership with GIRES to promote respect for trans people.


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