University of Bristol - School of Physiology, Pharmacology and Neuroscience
Research Associate/Senior Research Associate in Data Fusion for TORUS Programme
University of Bristol - School of Physiology, Pharmacology and Neuroscience, Bristol, Connecticut, us, 06010
Research Associate/Senior Research Associate in Data Fusion for TORUS Programme
Be among the first 25 applicants.
The role. The successful applicant will be based at the University of Bristol to work on the EPSRC TORUS Programme. A cure for Parkinson's disease has been held back for decades by the extreme difficulty of measuring whether proposed new drugs actually improve the patient's symptoms and daily life. TORUS aims to solve this through a novel platform of sensing technologies for use in patients' own homes along with an advanced data fusion and machine learning pipeline that measures changes in specific mobility-related behaviours over time. Thus, TORUS will create the capability to autonomously, continuously and objectively measure mobility-related symptoms of illness during the clinical trial of a new drug, in the patient's own home and for months at a time. TORUS will achieve this goal by using wrist-worn wearables integrated with AI-enabled cameras, led by codesign to ensure that decisions reflect the views and priorities of diverse patients & families.
What will you be doing?
Perform fundamental and applied research, within the TORUS data fusion and distributed machine learning team, in the key project area of human-behaviour analysis using spatiotemporal data from different sources and modalities.
Contribute to the design of the TORUS computational architecture, including the planning of data collection activities with patients.
Implement these procedures and techniques in the TORUS system.
Publish the work in top journals and international conferences.
Present the work in seminars and workshops as appropriate.
Attend regular project meetings.
Prepare progress reports for the TORUS management team and advisory board.
Advise on and participate in deployment activities related to the TORUS system.
Essential
PhD in machine learning (or working towards one for Grade I), data science, artificial intelligence or related research area.
Excellent and broad conceptual and practical knowledge of the state of the art in machine learning and data science.
Demonstrably excellent software development skills with Python and relevant libraries (scikit-learn, PyTorch/TensorFlow, and others).
Proven deep understanding of and demonstrable skills in data-driven experiments and performance evaluation.
First-authored publications on relevant topics in top-tier international conferences and workshops.
Excellent communication and presentation skills.
Proven ability to work both independently and as part of a team (TORUS is a very large project and team working will be a daily activity).
Proven ability to plan, manage and prioritise own workload while responding to the changing priorities and needs of a busy, dynamic environment.
Desirable
Track record in time series analysis or activity recognition for healthcare.
Interest in health applications of data science.
For Informal Queries Please Contact Telmo Silva Filho - telmo.silvafilho@bristol.ac.uk
Additional Information Contract type: Open ended with fixed funding for 18 months
Work pattern: Full time
Grade: I / J
Salary: Grade I £39,906 - £44,746 per annum; Grade J £43,482 - £50,253 per annum
School/Unit: School of Engineering Mathematics and Technology
This advert will close at 23:59 UK time on Thursday 20th November.
Interview dates will be confirmed in due course.
Our strategy and mission The University of Bristol aims to be a place where everyone feels able to be themselves and do their best in an inclusive working environment where all colleagues can thrive and reach their full potential. We want to attract, develop, and retain individuals with different experiences, backgrounds and perspectives – particularly people of colour, LGBT+ and disabled people - because diversity of people and ideas remains integral to our excellence as a global civic institution.
Available documents
ACAD108334 - Data Fusion for TORUS Programme - JD.pdf
Faculty of Science & Engineering Further Particulars 2024-25.pdf
#J-18808-Ljbffr
The role. The successful applicant will be based at the University of Bristol to work on the EPSRC TORUS Programme. A cure for Parkinson's disease has been held back for decades by the extreme difficulty of measuring whether proposed new drugs actually improve the patient's symptoms and daily life. TORUS aims to solve this through a novel platform of sensing technologies for use in patients' own homes along with an advanced data fusion and machine learning pipeline that measures changes in specific mobility-related behaviours over time. Thus, TORUS will create the capability to autonomously, continuously and objectively measure mobility-related symptoms of illness during the clinical trial of a new drug, in the patient's own home and for months at a time. TORUS will achieve this goal by using wrist-worn wearables integrated with AI-enabled cameras, led by codesign to ensure that decisions reflect the views and priorities of diverse patients & families.
What will you be doing?
Perform fundamental and applied research, within the TORUS data fusion and distributed machine learning team, in the key project area of human-behaviour analysis using spatiotemporal data from different sources and modalities.
Contribute to the design of the TORUS computational architecture, including the planning of data collection activities with patients.
Implement these procedures and techniques in the TORUS system.
Publish the work in top journals and international conferences.
Present the work in seminars and workshops as appropriate.
Attend regular project meetings.
Prepare progress reports for the TORUS management team and advisory board.
Advise on and participate in deployment activities related to the TORUS system.
Essential
PhD in machine learning (or working towards one for Grade I), data science, artificial intelligence or related research area.
Excellent and broad conceptual and practical knowledge of the state of the art in machine learning and data science.
Demonstrably excellent software development skills with Python and relevant libraries (scikit-learn, PyTorch/TensorFlow, and others).
Proven deep understanding of and demonstrable skills in data-driven experiments and performance evaluation.
First-authored publications on relevant topics in top-tier international conferences and workshops.
Excellent communication and presentation skills.
Proven ability to work both independently and as part of a team (TORUS is a very large project and team working will be a daily activity).
Proven ability to plan, manage and prioritise own workload while responding to the changing priorities and needs of a busy, dynamic environment.
Desirable
Track record in time series analysis or activity recognition for healthcare.
Interest in health applications of data science.
For Informal Queries Please Contact Telmo Silva Filho - telmo.silvafilho@bristol.ac.uk
Additional Information Contract type: Open ended with fixed funding for 18 months
Work pattern: Full time
Grade: I / J
Salary: Grade I £39,906 - £44,746 per annum; Grade J £43,482 - £50,253 per annum
School/Unit: School of Engineering Mathematics and Technology
This advert will close at 23:59 UK time on Thursday 20th November.
Interview dates will be confirmed in due course.
Our strategy and mission The University of Bristol aims to be a place where everyone feels able to be themselves and do their best in an inclusive working environment where all colleagues can thrive and reach their full potential. We want to attract, develop, and retain individuals with different experiences, backgrounds and perspectives – particularly people of colour, LGBT+ and disabled people - because diversity of people and ideas remains integral to our excellence as a global civic institution.
Available documents
ACAD108334 - Data Fusion for TORUS Programme - JD.pdf
Faculty of Science & Engineering Further Particulars 2024-25.pdf
#J-18808-Ljbffr