post-doctoral research associate
Imperial College London, City of Westminster
post-doctoral research associate
Salary not available. View on company website.
Imperial College London, City of Westminster
- Full time
- Temporary
- Onsite working
Posted 1 week ago, 8 Sep | Get your application in now before you're too late!
Closing date: Closing date not specified
Job ref: b1f673000a2945a1b9e8827a3d937bcd
Location ref: City of Westminster
Full Job Description
Applications are invited for the position of post-doctoral research associate, to work at the National Heart and Lung Institute, Imperial College London. We are a multi-disciplinary team consisting of researchers with strong backgrounds in clinical cardiology, cardiac electrophysiology, basic science, as well as AI, mathematical, engineering expertise. We are seeking a highly motivated post-doctoral research associate to join a collaborative team of clinicians, basic scientists, and physical scientists working on cardiovascular research. The post holder will apply signal processing and AI methodology to ECGs and 2-week single-lead ECG patch data, to predict a range of cardiovascular outcomes. The present post is funded by an EU Innovation Health Initiative (IHI), awarded to a global consortium/collaboration to reduce the burden of atrial fibrillation and advance its quantification and treatment. The work at Imperial College London is led by Professors Barbara Casadei, Fu Siong Ng and Steven Niederer. What you would be doing: You will apply signal processing and AI methodology to ECGs and 2-week single-lead ECG patch data, to predict a range of cardiovascular outcomes. You will work closely with the clinicians, biologists, bioengineers and physical scientists within the multi-disciplinary group.
You should have a PhD (or submitted a PhD and awaiting viva), or an equivalent qualification, industrial or commercial experience, in a computational discipline.
- Candidates who have not yet been officially awarded their PhD will be appointed as a Research Assistant within the salary range £43,863 - £47,223 per annum. Experience in computer programming (particularly Python), is essential, and previous experience with AI research is highly desirable. A background in cardiovascular research is also desirable. You should also have a collaborative approach to research as this role requires working with other groups both within and outside the department., Senior (5+ years of experience) Tagged as: Academia, Machine Learning, NLP, United Kingdom
Imperial College London, Imperial College London is a university with a mission to benefit society through excellence in science, engineering, medicine and business.
The post is full-time fixed term for a duration of 2 year and based at the Hammersmith Campus, with the possibility of extension. The opportunity to continue your career at a world-leading institution and be part of our mission to continue science for humanity. Grow your career: gain access to Imperial's sector-leading dedicated career support for researchers as well as opportunities for promotion and progression. Sector-leading salary and remuneration package (including 41 days off a year and generous pension schemes). Be part of a diverse, inclusive and collaborative work culture with various staff networks and resources to support your personal and professional wellbeing., The post is full-time fixed term for a duration of 2 year and based at the Hammersmith Campus, with the possibility of extension. Informal enquiries may be sent to Prof Fu Siong Ng () About Imperial Welcome to Imperial, a global top ten university where scientific imagination leads to world-changing impact. Join us and be part of something bigger. From global health to climate change, AI to business leadership, we navigate some of the world's toughest challenges. Whatever your role, your contribution will have a lasting impact. As a member of our vibrant community of 22,000 students and 8,000 staff, you'll collaborate with passionate minds across nine London campuses and a global network. £49,017 to £55,144 per annum
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