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- Tasks: Develop machine learning models for cardiac devices and collaborate with clinicians.
- Company: Join the British Heart Foundation, a leader in cardiovascular healthcare innovation.
- Benefits: Enjoy 41 days holiday, pension scheme, and employee assistance programmes.
- Why this job: Make a real impact on patient care with cutting-edge technology in a diverse environment.
- Qualifications: Post-doctoral experience in machine learning and data analysis required.
- Other info: Flexible working arrangements available; commitment to diversity and inclusion.
The predicted salary is between 36000 - 60000 £ per year.
About us
We are advertising a data scientist position at the British Heart Foundation. This role offers an exciting opportunity to work on a research project focused on advancing machine learning techniques for cardiac electrophysiology and cardiac implants, utilizing unique clinical data. The goal is to translate research findings into clinical care (\’AI for pacemakers\’). The position is initially for two years full-time, with the possibility of part-time arrangements. It is based at the UCL Institute of Cardiovascular Science (ICS) with the main clinical base at Barts Heart Centre (BHC), St Bartholomew\’s Hospital. UCL ICS and BHC are renowned institutions dedicated to translating machine learning innovations into cardiovascular healthcare for a population of six million.
About the role
The post involves developing and applying machine learning models for use in pacemakers and implantable cardioverter-defibrillators (ICDs). It leverages a unique dataset from the largest population of patients with cardiac implantable electronic devices in the UK, along with advanced modeling and outcomes from population-based registries. The position is funded through an academic research grant awarded to UCL by the British Heart Foundation for 24 months, full-time.
About you
- Undertake a post-doctoral research project focused on developing machine learning models for cardiac electrophysiology.
- Develop and curate complex time series datasets, including data labeling strategies.
- Create and maintain Python-based tools and workflows for data integration, model simulation, and analysis.
- Collaborate closely with clinicians to align computational findings with clinical outcomes.
What we offer
- 41 days holiday (27 days annual leave, 8 bank holidays, and 6 closure days)
- Additional 5 days\’ annual leave purchase scheme
- Defined benefit career average revalued earnings pension scheme (CARE)
- Cycle to work scheme and season ticket loan
- Immigration loan
- Relocation scheme for certain posts
- Enhanced maternity, paternity, and adoption pay
- Employee assistance programme: Staff Support Service
- Discounted medical insurance
Visit https://www.ucl.ac.uk/work-at-ucl/reward-and-benefits to find out more.
Our commitment to Equality, Diversity and Inclusion
As London\’s Global University, we value diversity as a source of creativity and innovation. We are committed to providing equal opportunities, fostering fairness, and creating an inclusive environment where everyone feels they belong. We particularly encourage applications from candidates who are underrepresented at UCL, including those from Black, Asian, and ethnic minority backgrounds, disabled people, LGBTQI+ individuals, and women in Grade 9 and 10 roles. More about our commitment can be read at https://www.ucl.ac.uk/equality-diversity-inclusion/.
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Post-doctoral Position in Machine Learning and Cardiology employer: UCL
Contact Detail:
UCL Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Post-doctoral Position in Machine Learning and Cardiology
✨Tip Number 1
Familiarise yourself with the latest advancements in machine learning, particularly in the context of cardiac electrophysiology. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the field by attending relevant conferences or seminars. Engaging with experts can provide insights into current challenges and innovations, which could be beneficial when discussing your ideas and experiences.
✨Tip Number 3
Consider reaching out to current or former employees at UCL or the British Heart Foundation. They can offer valuable information about the work culture and expectations, helping you tailor your approach when applying.
✨Tip Number 4
Stay updated on the unique dataset mentioned in the job description. Understanding its significance and how it can be leveraged for machine learning applications will demonstrate your genuine interest and preparedness for the role.
We think you need these skills to ace Post-doctoral Position in Machine Learning and Cardiology
Some tips for your application 🫡
Understand the Role: Read the job description thoroughly to grasp the specific requirements and responsibilities of the post-doctoral position. Highlight your experience in machine learning and cardiology, ensuring you align your skills with the role's focus on cardiac electrophysiology.
Tailor Your CV: Customise your CV to reflect relevant experiences, particularly in developing machine learning models and working with clinical data. Emphasise any previous research projects or collaborations with clinicians that demonstrate your ability to translate findings into clinical applications.
Craft a Compelling Cover Letter: Write a cover letter that not only outlines your qualifications but also expresses your passion for advancing healthcare through technology. Mention specific projects or achievements that relate to the use of AI in pacemakers and how they can contribute to the goals of the British Heart Foundation.
Highlight Collaboration Skills: Since the role involves close collaboration with clinicians, make sure to showcase your teamwork and communication skills. Provide examples of how you've successfully worked in interdisciplinary teams to achieve research objectives.
How to prepare for a job interview at UCL
✨Understand the Research Focus
Make sure you have a solid grasp of the specific research project related to machine learning and cardiac electrophysiology. Familiarise yourself with current advancements in AI for pacemakers and how they can impact clinical care.
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and any relevant machine learning frameworks. Highlight specific projects where you've developed or applied models, especially in healthcare or time series data.
✨Emphasise Collaboration
Since the role involves working closely with clinicians, be ready to talk about your teamwork experiences. Share examples of how you've successfully collaborated with others to align technical findings with practical applications.
✨Prepare Questions
Have thoughtful questions ready about the role, the team, and the research environment. This shows your genuine interest in the position and helps you assess if it's the right fit for you.
