Are you looking for a working student opportunity? We’re looking to recruit a working student to join us by working upto 20 hours per week for a period of 6 months initially; at our Computational Pathology site, Munich. Would you like to gain experience in supporting our development of image analysis applications, which impacts management workflows around our deep learning-based image analysis pipeline? You will be working with highly skilled experts in biology, image analysis and software engineering. If this sounds like a position that you are excited about; then AstraZeneca might be the one for you!
AstraZeneca is a global, science-led, patient-focused biopharmaceutical company that focuses on the discovery, development and commercialisation of prescription medicines for some of the world’s most serious diseases. But we’re more than one of the world’s leading pharmaceutical companies. At AstraZeneca we’re dedicated to being a Great Place to Work. Where you are empowered to push the boundaries of science and unleash your entrepreneurial spirit. There’s no better place to make a difference to medicine, patients and society.
Welcome to Computational Pathology Munich, one of over 400 sites here at AstraZeneca, providing a collaborative environment where everyone feels comfortable and able to be themselves is at the core of AstraZeneca’s priorities, it’s important to us that you bring your full self to work every day. To help you maintain your best self, here’s a sneak peek into some of the things this site provides for you: After-work events, Lunch & Learns, Bright and spacious environment, Sustainable office working environment, Networking events, family and childcare support and of course the Alps around the corner for hiking, biking and skiing.
Be part of fulfilling our ambition to be world leaders in Oncology. We are already the fastest growing team within AstraZeneca and across the industry, and there are countless new indications and targets in our game-changing pipeline. Here we’re on a journey to becoming digitally-enabled, to discover new ways of offering better solutions to our patients. Join the team with a vision to use data as a tool, to build a better, deeper, more personal understanding of the people we’re helping. To ultimately deliver better outcomes for them – through dynamic omnichannel content, personal relationships and experience.
What you’ll do
The Image Data Science Team is looking for motivated working students to support our development of deep learning based image analysis algorithms. There is a strong focus on algorithmic research in deep learning with focus on computer vision algorithms for detection and segmentation in histopathological images. Your role includes the following:
Support design and implement new computer vision algorithms for histopathology images optimized for speed and robustness.
High-quality code development: write well documented code with automated tests
Work in a multi-disciplinary team with experts in biology, image analysis and software engineering
Essential for the role
Registered student in Computer Science or similar university degree
Strong skills in Python or another common programming language
Independent style of working
Excellent communication and conflict resolution skills
English language skills
Desirable for the role
Completed undergraduate degree in Computer Science or similar
Familiarity with image analysis and deep-learning
Familiarity with concepts for semantic, instance and panoptic segmentation
Hands-on experience with tensorflow/pytorch
Experience with VC (e.g., git)
Competitive salary package and benefits
Close Date: 22/0/2022
At AstraZeneca we’re dedicated to being a Great Place to Work. Where you are empowered to push the boundaries of science and unleash your entrepreneurial spirit. There’s no better place to make a difference to medicine, patients and society. An inclusive culture that champions diversity and collaboration, and always committed to lifelong learning, growth and development. We’re on an exciting journey to pioneer the future of healthcare.
So, what’s next?
If you’re curious to know more then please reach out to Louise Bennett
Where can I find out more?
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