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Synthetic Biology in Cambridge

 

Post-doctoral researcher position available at Microsoft Research. Developing new and augment existing machine learning methods for applications in the life sciences (e.g., in medical image analysis or drug design and manufacturing).

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  • Deadline: Not specified

  • Salary: Not specified

  • Position Type: Full time

  • Location: Microsoft Research, Cambridge

Microsoft Research Cambridge (UK) is looking for exceptional Researcher candidates working on applications of machine learning to the life sciences. The successful applicant will be expected to develop new and augment existing machine learning methods for applications in the life sciences (e.g., in medical image analysis or drug design and manufacturing). This is an exceptional opportunity to drive ambitious research while collaborating with partner companies and the product teams of one of the largest software companies in the world.

Microsoft AI and Research works with the world's best researchers, moving with the current of technology as it rapidly evolves. Together we share the motivation to seek innovative solutions to the world's toughest challenges and improve the lives of people everywhere. The Microsoft Research Cambridge lab hosts over 150 full-time researchers and engineers who collaboratively pursue research on machine learning, systems and networking, programming languages, synthetic biology, medical imaging and human experience and design.

In this role, you will interact with a team of experts in machine learning, deep learning, software development and with partners with backgrounds in medicine, chemistry and pharmacology.

Your responsibilities will include:

• Inventing new, efficient machine-learning models for the quantitative analysis of (noisy) data obtained from medical devices, lab measurements and user studies.
• Testing and evaluating such models quantitatively and comparing them to existing algorithms on both bespoke and public datasets.
• Working with software engineers to integrate your research into libraries and tools used by our collaborators.
• Engaging with external collaborators to shape your research agenda for maximal impact and relevance.
• Publishing your work at top conferences and journals such as NeurIPS, MICCAI, Nature, etc.

Required Qualifications:

• Expert understanding of state-of-the-art machine learning techniques, evidenced by a strong publication record in relevant conferences (e.g., NeurIPS, ICLR, ICML, …) or product development.
• Hands-on experience with current machine learning frameworks (e.g., TensorFlow, PyTorch, or DyNet).
• Interest in deep research with high real-world impact.
• Completed PhD (or close to completion of PhD).

Preferred Qualifications:

• Hands-on experience of analysis of noisy medical data (e.g., medical images, wet lab data, …)
• Demonstrable passion for data, with strong experience with data management and curation.
• Ability to conduct well designed and reproducible experiments.
• Ability to communicate machine learning results to a non-expert audience.
• Strong intellectual curiosity and passion to apply innovative ideas to solve real-world problems for enterprises and consumers.
• Ability to think beyond machine learning metrics and focus on customer needs and patients’ outcomes.

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