About the Department
The AI and Digital Research department (AIDR) is a global, multidisciplinary team that puts AI at the center of drug discovery. The department takes a human-centric approach to drug discovery, utilizing cutting-edge data science, machine learning, and engineering techniques to identify novel targets, biomarkers, and new drugs. By doing so, they aim to accelerate the drug discovery process and unlock a deeper understanding of disease and treatment outcomes.Through close collaboration with other departments and teams across the organization, the AI and Digital Research department works to bring innovative therapies to patients more quickly and improve the lives of those living with chronic conditions. With a focus on putting AI at the forefront of drug discovery, the department is dedicated to revolutionizing the pharmaceutical industry and bringing life-changing treatments to those who need them most.
The Vice President (VP), Computational Drug Design (CDD) will develop, lead and grow a computational drug design department that delivers high quality insights to guide decision making in Research & Early Development (R&ED) and Development. The role will devise and execute on a computational drug design strategy to be implemented across R&ED and Development, drive the delivery of the cross-SVP strategy through a leadership team, ensure a strong culture of sharing knowledge on computational drug design across SVP areas. The VP will have overall scientific responsibility for delivering consistent high quality computational drug design analyses across R&ED and Development, define and implement the growth strategy, and ensure strategic investment in computational drug design data and platforms is delivered.
Reports to the Corporate Vice President for AI & Digital Research (AIDR). Leads the Computational Drug Design unit through other leaders.
Engagement with SVPs and their management teams through presentations, 1:1 meetings and in-person visits to demonstrate the value of in silico approaches and its integration in their decision-making activitiesDirect engagement with scientists and researchers on the ground with outreach around computationally validated targets and biomarkers through 1:1 meetings, learn more sessions, workshops, and drop-in sessionsEngage early with project and portfolio managers through in-person meetings and virtual meetings to include in silico models and approaches in early-stage pipeline projectsEngagement with across relevant EVP areas (DDIT, Data science) active participation in meetings and joint leadership meetingsEarly engagement and influencing of research projects to enable in silico approaches becoming critical decision-making resource rather than a tick-box exerciseRegular participation in relevant (international) computational drug design forumsEngage with local and international universities and research institutions to influence research, develop collaborations, training of students and recruitment activities in computational drug design and related fieldsEngage with biotech’s and technology companies around potential platforms and tools, including AI and machine learningEnsures global scalability of solutions and understands the importance of involving various global stakeholders. Considers the impact of decisions and initiatives on other areas of the organizationAll R&ED sites are within scope of the responsibility of the role. Internal collaborations across all R&ED sites will deliver value in silco approaches in a co-creation frameworkEmployees in the VP area are located at international sites e.g. Denmark, UK, Boston, Seattle. Expansion to new sites (south America, Barcelona) as a future footprint activityDirect influence on research activities in different geographies through providing expert knowledge drug discovery, applied AI, drug design (antibody/peptide/protein engineering) to inform internal research activities and external collaborationsCollaborate with other pharmaceutical companies and organizations around potential computational drug development-based initiativesNavigate the proprietary nature of some computational solutions offered by external vendors
- Key stakeholders:
- R&ED Senior Vice President (SVP) area management teams
- R&ED SVP area Line oof Business (LoB) scientists
- Project Vice Presidents (PVP)
- Development SVP area management teams
- Development SVP LoB scientists
- University groups
- Other pharma companies
- External biotech’s with platforms omics, spatial biology capabilities or AI based capabilities
- Develop and lead the AIDR Computational Drug Design department: Set up and lead a cutting-edge computational drug design unit that serves as a key resource for drug discovery. This includes creating a collaborative environment where new ideas and technologies can be nurtured and applied to identify novel therapeutic designs and modalities. The leader will also work to optimize resources and streamline processes, leading to faster and more cost-effective drug design cycles. The VP will work to secure buy-in across SVP and EVP areas and integrate computational drug design approaches into all relevant projects, while also working to establish the unit as the industry leader externally
- Develop and implement computational strategies for hit identification, lead optimization, and candidate selection across multiple therapeutic areas, with a focus on biologics and protein engineering.
- Lead a team of data scientists, computational chemists, and biologists to design and execute computational experiements and models to guide drug discovery efforts
- Collaborate closely with other departments, such as chemistry, pharmacology, biophysics and recombinant technologies to integrate computational appoaches with experimental data and to advance drug discovery programs
- Apply data science and machine learning techniques to analyze large and complex datasets, identify patterns and trends, and make data-driven decisions
- Drive culture of experimentation, innovation, and continuous learning, and establish matrics and KPIs to measure the impact and ROI data science and machine learning initatives
- Stay up-to-date with the latest developments in computational drug design and related fields, and apply new methods and technologies to improve drug discovery processes and outcomes
- Build and maintain strong relationships with external partners and academic institutions to access cutting-edge computational tools and expertise
- Devise and execute on a computational drug design strategy: Responsible for developing and implementing a strategy that leverages latest AI methods to help advance molecular design to drive value across SVP areas and achieve R&D goals. This includes identifying key areas of focus and implementing state-of-the-art methods and approaches to inform decision making and drive innovation in the drug pipeline. The VP will also work to foster collaboration between computational drug discovery teams and other stakeholders across EVP areas to drive innovation and advance the pipeline
- Scientific responsibility within the VP area: Ensure that project data is analyzed and interpreted appropriately to design campaigns, inform decision making in the API strategy and project gate ways. The VP will also provide scientific leadership the CDD department and AIDR sub departments (e.g., Machine Intelligence, Research Engineering), to deliver state-of-the-art, high-quality deliverables that span across SVP areas and drive innovation in drug discovery. The VP will also play a key role in supporting early innovation by delivering high-quality novel computational discoveries to R&D and will be involved in international collaborations with key external partners in early discovery. Lead the development and implementation of computational methods for the design and optimization of Antibodies, RNA, peptide and protein therapeutics
- Ensure appropriate investment in enablers of computational drug design research: Responsible for investigating and implementing state-of-the-art computational, platforms and technologies to accelerate drug discovery and innovation. This includes working with external partners in industry and academia to stay ahead of the curve in terms of computational drug design methods and platforms
- Organizational change management, new talent hires, communication, training and development: Responsible for managing organizational design, development, communication and training within the unit. This includes communicating frequently with key stakeholders, creating training courses and internal conferences to build a community of advocates and interpreters within the company, and actively recruiting diverse talent to bring new perspectives and ideas to the unit
- Management tasks: Ensure the area delivers according to the Novo Nordisk annual wheel for line activities e.g. Performance management (input to CVP Balance Score Card (BSC), target setting for own area); Secure an optimal utilization of resources and equipment by monitoring organizational performance; Drive continuous improvements in the area to meet business goals; Ensure budget and business targets are met; Responsible for Occupational Health & Safety in the area; Estimates of resource demand and bottlenecks, secure an optimal utilization of resources and equipment in collaboration with department heads
- Consistently works with complex issues that require broad-based sustainable solutions involving other functions across NN. Builds capability across the function to develop short- and long-term priorities consistent with Novo Nordisk’s strategy. VP should have demonstrated significant results and experiences as both a senior director and project manager in an innovative matrix organization. VP should have demonstrated consistent innovative novel approaches including impact beyond their area of remit
- Represent Novo Nordisk at large international conferences and events related to computational drug design and machine learning, such as International Conference on Learning Representation (ICLR), The Conference and Workshop on Neural Information Processing Systems (NeurIPS). Drive greater exposure of Novo Nordisk's AI enabled drug design efforts through publications in peer-reviewed journals and presenting at conferences and events. Represent Novo Nordisk on various joint steering committees for international partnerships and collaborations in the field of Machine learning and computational drug design. Share knowledge and expertise internally through various forums such as the data science academy, learn more sessions and local engagement
10-20% overnight travel required.
Development Of People
Supervisory, ensure that reporting personnel have individual development plans (IDP), with annual goals and measurements that are consistent with the priorities of the business, and that interim reviews are held so that their work is focused on those priorities, and they understand their level of accountability for results and the measurement process. Ensure that the IDP forms include completed learning and aspiration plans and are in place for all reporting personnel to enable the achievement of goals and capability to assume increased levels of responsibility. Manage the application and communication of all Novo Nordisk policies, procedures, and Novo Nordisk Way.
- MSc in chemistry, bioinformatics, computer science, or a related field is highly desirable. PhD desirable.
- At least 10 years of experience in computational modelling in the pharmaceutical or biotech industry, with a focus on biologics and protein engineering
- Proven track record of leading and managing computational drug discovery programs
- Strong computational skills and hands-on experience with molecular modelling techniques, such as molecular docking, molecular dynamics simulations, and homology modelling
- Experience with data science and machine leanring techniques applied to drug design
- Proven track record of leading successful drug discovery and development projects, ideally in the pharmaceutical or biotech industry
- Deep expertise of drug discovery and/or development from work within a pharmaceutical, biotech or related company
- Proven track record of working with cross-functional teams
- Strong record of publications in peer-reviewed journals and presentations at relevant conferences
- Experience with managing budgets and resources for drug discovery and development projects
- Strong understanding of the IP/regulatory environment for drug discovery and development
- Previous supervisory experience required
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.
Novo Nordisk is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, gender identity, sexual orientation, national origin, disability, protected veteran status or any other characteristic protected by local, state or federal laws, rules or regulations.
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