Senior Data Scientist

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Would you like to leverage your statistical skills within a machine learning framework to help identifying new drug candidates for cardiometabolic diseases and optimize our high throughput assays for this purpose? Are you motivated by making exact biophysical and biochemical models and rigorous quantification methods available to our experimental colleagues to support design of novel therapeutics and being part of a team committed to engaged and inspiring collaborations while working on hard problems? Then you may be the new colleague we are looking for to join our Machine Intelligence Department. The position As a data scientist you will report to the head of Machine Intelligence. Internal partners include specialists, engineers, software developers, technology scouts & partnership developers, system engineers, designers, medical doctors, IT professionals, and others across DK and other countries. As an expert in techniques within Bayesian statistics, machine learning and active learning, you will bring your expertise in using these models to enhance the efficiency and precision of our high throughput biophysical, biochemical, or biological assays, connecting the results to multi-omics data analyses and provide support to our design of new experiments. You will work within drug development, target discovery projects and biophysical and pharmaco-kinetical characterization of our drug molecules. This requires close collaboration with other research scientists in multidisciplinary teams and solving ambitious scientific goals. The position also requires close collaboration with our data science and machine learning colleagues across global sites and contributing to the onboarding and development of new methods within Machine learning and AI.
  • Develop state-of-the-art statistical models for quantification of high throughput bio-physical/chemical, pharmacological or biological assays.
  • Apply active learning methodologies in design of experiments, and statistical methods to multi-omics and multi-modal data analyses.
  • Collaborate with multidisciplinary teams to design and execute experiments that support drug development/screening projects in early research.
  • Stay current with the latest research and advancements in the field of statistics, stochastic programming, active learning and Bayesian optimization.
  • Communicate findings and results to stakeholders through presentations, reports, and scientific publications.
  • Qualifications To succeed in this role, you have:
  • Master’s degree with 3+ years’ relevant experience, or PhD with little to no years’ relevant experience, OR Bachelor’s degree with 5+ years’ relevant experience can be considered with strong background in Bayesian statistical methods and active learning techniques.
  • Strong proficiency in Python and experience with stochastic programming frameworks (e.g., BoTorch, numpyro, pyMC4).
  • Familiarity with bio-physical/chemical methods (e.g., reaction kinetics, thermodynamics, protein structure characterization).
  • Experience with modern version control and continuous integration / testing systems, such as GitLab / GitHub.
  • Excellent problem-solving, communication skills and the ability to work independently as well as in a team environment.
  • Preferred Qualifications:
  • Experience with causal analysis, inference, and in multi-omics data analysis.
  • Experience in writing well-tested and documented code, adhering to best practices in software development.
  • Experience working with cloud compute services such as AWS, Azure, or Nvidia DGX Cloud.
  • You will have the freedom to drive collaborations, be innovate in statistical techniques, and shape group strategies. Show success through strategic innovation, mentoring, proposing new models, and driving collaborations. Desire to learn, collaborate, and share across diverse backgrounds. About the department The Machine Intelligence department is part of our AI and Digital Research (AIDR) area, where we apply and develop state-of-the-art capabilities in computer vision, deep learning, and AI/ML approaches for biological knowledge representation, target identification and validation, drug design, causal analysis, and design of experiments. We invent novel medicines by applying advanced computational techniques and developing innovative computational methods. We also engage in external collaborations to ensure access to cutting-edge research and technology.
    We collaborate closely with our experimental colleagues in early research to improve and accelerate the discovery, validation, and design of new drug candidates. With a team of scientists within foundational statistics that strive to deliver the latest advancements in statistical tools for high throughput analysis, active learning, multi-objective optimization and causal inference to benefit patient health and global medicine. Digital Science & Innovation (DSI) is supporting the digital journey across all our therapy areas in R&ED. In DSI, we work in multidisciplinary teams – in strong collaboration with all areas across R&ED and R&ED IT. We participate in drug development projects across the value chain, from early discovery to pre-clinical development. We engage in external collaborations to ensure access to the latest research and technology enablers, and we automate our labs and processes, and we focus on developing and retaining top talent. Working at Novo Nordisk At Novo Nordisk, we don't wait for change. We drive it. We're a dynamic company in an even more dynamic industry, and we know that what got us to where we are today is not necessarily what will make us successful in the future. We embrace the spirit of experimentation, striving for excellence without fixating on perfection. We never shy away from opportunities to develop, we seize them. From research and development, through to manufacturing, marketing, and sales - we're all working to move the needle on patient care. Contact
    For further information, please contact scientific director Jesper Ferkinghoff-Borg on +45-30777217 or via email: [email protected] Deadline 19 September 2023 To apply for this position, please submit your CV, cover letter, and a list of relevant publications. We look forward to reviewing your application and exploring the potential for you to contribute to our dynamic and innovative team. 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.


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    Jobbet er oprettet på vores service den 29.8.2023, men kan have været deaktiveret og genaktiveret igen.

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