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- Tasks: Research and develop machine learning methods for medical image analysis.
- Company: Join a leading healthcare tech company focused on innovation.
- Benefits: Gain hands-on experience, mentorship, and exposure to cutting-edge technology.
- Other info: Diverse and inclusive workplace with opportunities for personal and professional growth.
- Why this job: Make a real impact in healthcare while working with advanced data science techniques.
- Qualifications: Studying or recently graduated in Data Science, Computer Science, or related fields.
The predicted salary is between 20000 - 30000 £ per year.
We are looking for a motivated and enthusiastic Data Science (Cardiac) Intern to join our growing Data Science team. This is an exciting opportunity to work on cutting edge machine learning and deep learning applications for large scale medical image analysis.
About The Role
As a Data Science (Cardiac) Intern, you will support the wider team in researching new methods and algorithms for both internal and external projects. You will contribute to validating prototypes and help translate research into real-world products by collaborating with multidisciplinary teams across the organisation. There is a particular focus on the implementation of state-of-the-art deep learning models for medical imaging, including working with large datasets in cloud-based environments.
Day to day your duties will include:
- Conduct research and development of machine learning methods for medical image analysis
- Support the team with technical reports and algorithm specifications
- Collaborate with Imaging Science, Physics, Clinical Science, and Biomarker teams on algorithm development and analysis
- Assist in the validation and optimisation of models for existing and future products
- Work with large-scale datasets using cloud technologies (e.g. AWS)
- Stay up to date with the latest advancements in machine learning and image analysis
- Support the team with ad hoc tasks as required
About You
Currently studying or recently completed a degree in Data Science, Computer Science Engineering, Physics, or a related field. Strong programming skills, ideally in Python. Strong analytical thinking and problem-solving abilities. Ability to work effectively in a collaborative, multidisciplinary team environment.
If you're excited by data, driven by impact, and want to work on meaningful problems in healthcare, we’d love to hear from you. At Perspectum, we are committed to fostering diversity, equity, and inclusion. We prioritise hiring based on merit, skills, and qualifications, valuing individuals for their unique contributions while ensuring a culture that respects and celebrates differences. If you require any reasonable adjustments as part of your application process, please let our Talent Team know.
Data Science (Cardiac) Intern in Oxford employer: Perspectum Ltd
Contact Detail:
Perspectum Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science (Cardiac) Intern in Oxford
✨Tip Number 1
Network like a pro! Reach out to current or former employees on LinkedIn and ask about their experiences. A friendly chat can give you insider info and might even lead to a referral.
✨Tip Number 2
Show off your skills! If you’ve worked on any relevant projects, create a portfolio or GitHub repository to showcase your work. This is a great way to demonstrate your programming skills and analytical thinking.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss machine learning methods and algorithms, especially those related to medical image analysis. Practice common interview questions with friends or mentors.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining our team at Perspectum.
We think you need these skills to ace Data Science (Cardiac) Intern in Oxford
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Science (Cardiac) Intern role. Highlight relevant skills like programming in Python and any experience with machine learning or medical imaging. We want to see how your background fits with what we're doing!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for data science and healthcare, and explain why you're excited about this internship. We love seeing enthusiasm and a genuine interest in our work.
Showcase Your Projects: If you've worked on any projects related to data science, especially in medical imaging or machine learning, make sure to mention them. We’re keen to see how you’ve applied your skills in real-world scenarios!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about what we do at StudySmarter.
How to prepare for a job interview at Perspectum Ltd
✨Know Your Stuff
Make sure you brush up on your knowledge of machine learning and deep learning, especially as it relates to medical image analysis. Familiarise yourself with the latest advancements in these fields, and be ready to discuss how they can be applied in real-world scenarios.
✨Show Off Your Skills
Prepare to demonstrate your programming skills, particularly in Python. You might be asked to solve a coding problem or explain your thought process behind a project you've worked on. Have examples ready that showcase your analytical thinking and problem-solving abilities.
✨Collaboration is Key
Since this role involves working with multidisciplinary teams, be prepared to discuss your experience collaborating with others. Think of specific examples where you’ve successfully worked in a team environment, and how you contributed to achieving a common goal.
✨Ask Smart Questions
At the end of the interview, don’t forget to ask insightful questions about the team, projects, and company culture. This shows your genuine interest in the role and helps you determine if it's the right fit for you. Consider asking about the types of datasets you'll be working with or the challenges the team is currently facing.