Lead Research Scientist: AI & Machine Learning

Category:  Research
Location: 

Oxford, South East, GB

   

Would you like to leverage your experience in machine learning and curiosity about the actionable insights that AI can draw in life sciences? Are you motivated by driving functional strategies and being part of a multi-disciplinary team committed to having fun while identifying new drug targets for cardiometabolic disease? Then you may be the new colleague we are looking for to join our Computational Biology Department. We encourage you to apply!

 

The Position

In this senior scientific position, you will be expected to define and drive efforts utilising cutting edge ML/AI across numerous areas of active research. You will help lead efforts to gain molecular insights from in-vitro data and deeply integrate cellular and patient imaging into our discovery process, including making predictions from longitudinal patient data.

 

A substantial emphasis in the position is discovery of novel drug targets for cardiometabolic disease. To get us there, you will be:

  • Able to leverage your Machine Learning experience applied to heterogenous semi-structured data to develop models that fully leverage multi-scale contextual information.
  • Skilled with a variety of Machine Learning methods, including deep learning. 
  • Driven by the desire to understand these models and identify features/interactions in the data that will help us develop the next generation of treatments.
  • Given the freedom to build internal and external collaborations, explore novel data and methodologies, and participate in strategic decision making.
  • Able to demonstrate mastery in methodological advances within an organisation, contributing to strategic innovation in the group, mentoring young scientists, proposing, and presenting new target candidates. Moreover, advancing showcases of precision medicine, producing scientific publications and driving collaborations to pre-defined endpoints.

 

Qualifications

To be successful in the role you will have a PhD and at least 6 years of postdoctoral academic/industry experience in an AI/ML related discipline, ideally applied to biology/healthcare.  You will be able to demonstrate scientific leadership in developing robust AI/ML models and be able to independently lead programs and small teams to deliver insights from heterogeneous data.  You will have strong programming skills (in Python or R), substantial machine-learning experience, and experience working cross-functionally with stakeholders with various academic backgrounds.

You will demonstrate:

  • Expertise in a variety of deep-learning (CNN, GAN, transformers) and other ML methods (GBM, SVM, RF) and an ability to lead both projects and junior scientists in training and evaluating such models
  • Having independently driven projects preferably in collaborative settings, published and presented in international contexts and demonstrated coordination capabilities
  • Experience with biological data including genetic, transcriptomic, and other functional-genomic data (highly valued)
  • Prior experience in industry or clinical contexts (strongly preferred).
  • Personally, you enjoy working in teams, and are driven by independently creating value for the organisation. You are conscientious and able to contribute to a positive working environment on site.

 

About the Department

You will join the Computational Biology Department at Novo Nordisk Research Centre Oxford (NNRCO), located at Oxford University’s Old Road Campus.  The group boasts significant expertise across a diverse set of disciplines in machine learning, computational biology, and knowledge graphs.  In addition to staff scientists, our group hosts and collaborates with researchers from Oxford University and we undertake a number of ambitious academic and in-house projects.  Our focus is drug-target identification and providing insights from heterogenous data sources.  We share an excitement about applying novel data science ideas and technologies to rich and complex data towards biological and clinical insights.

 

NNRCO is Novo Nordisk’s research centre, focused on biology and target discovery across the broad spectrum of cardiometabolic disease. We use genetics, functional genomics, human-centric disease models and computational biology to develop an unparalleled understanding of cardiometabolic disease and deliver therapies that transform the lives of patients. You can read more about Novo Nordisk Research Centre Oxford at: http://www.novonordisk.co.uk/about-novo-nordisk-in-uk/oxford-research-centre.html

 

Working at Novo Nordisk

Novo Nordisk is its people. We know that life is anything but linear and balancing what is important at different stages of our career is never easy. That’s why we make room for diverse life situations, always putting people first. We value our employees for the unique skills they bring to the table, and we work continuously to bring out the best in them. Working at Novo Nordisk is working toward something bigger than ourselves, and it’s a collective effort. Novo Nordisk relies on the joint potential and collaboration of its more than 40,000 employees. Together, we go further. Together, we’re life changing.

 

Contact

For further information, please contact Dr. Robert Kitchen +44-7775-006813, jzrk@novonordisk.com or Dr. Ramneek Gupta, on +44-7824606773, rmgp@novonordisk.com

 We offer flexibility in location across Oxford UK, Måløv Denmark, and Boston USA.

 

Deadline

Apply before 09/12/2022

 

We commit to an inclusive recruitment process and equality of opportunity for all our job applicants. 

 

At Novo Nordisk we recognize that it is no longer good enough to aspire to be the best company in the world. We need to aspire to be the best company for the world and we know that this is only possible with talented employees with diverse perspectives, backgrounds and cultures. We are therefore committed to creating an inclusive culture that celebrates the diversity of our employees, the patients we serve and communities we operate in. Together, we’re life changing.