About the Department
Our global department is anchored within Global Drug Discovery (GDD) in Research & Early Development (R&ED) with scientists based both in Måløv and Boston, supporting our portfolio with pharmacokinetic (PK) and pharmacodynamic (PD) evaluations using a variety of modelling and simulation tools. Mechanistic modelling (QSP) is an important part of our capabilities. The models we develop and apply help to understand resistance mechanisms, support drug discovery, optimize dose & schedule selection and combination therapy and much more.
The Position
In this role, you will combine your expertise in modelling and simulation with cutting edge pharmacology (both clinical and pre-clinical) and bioengineering and provide scientific leadership in advancing novel therapies to the clinic with minimal non-clinical in vivo studies. Indeed, you will be part of a growing team that collectively drives the implementation of humanized pre-clinical research (MPS) and connects the insights and output to biobanks/clinical trial data, and vice versa. This requires efficient collaboration and communication with other subject matter experts. Mathematical modelling is crucial to bridge the translational gap, e.g. by tailormade modeling of the MPS system and the relevant human physiology, and will inform and support drug discovery, development and regulatory interactions.
Relationships
You will be reporting to the Head of Discovery PKPD and QSP modelling, a recently established department to support the therapeutic areas of NN. You will work closely with highly skilled and dedicated colleagues supporting projects from early discovery, through non-clinical development, as well as early clinical development. In our daily work, we have close collaboration with all parts of the global Discovery and Development organization, research project teams as well as external collaborators. Key stakeholders include experimental scientists, project managers and, through presentation of your work at decision meetings, senior managers (VP+ level).
Essential Functions
- Identification of the current knowledge gaps and outstanding questions and converting the relevant biology, biophysical MPS setups, and question(s) into mathematical formulation that can be addressed with modeling and simulation.
- Being an innovator within QSP and driver of collaborations with MPS bioengineers, scientists, and clinicians to solve unique and complex problems, enabling closure of translational gaps.
- Anticipating internal and/or external business challenges and issues; recommending process, product or service improvements.
- Regularly leading project teams to achieve milestones and objectives.
- Contributing to the development of functional strategies to foster innovation within and to the NN pipeline.
We value diversity! So, no matter whether you have modelled climate/weather, ecology, biological networks or other natural processes we would like to hear from you!
Qualifications
- Ph.D. and 10+ years of post-doctoral experience and at least 5 years in an industry setting; Master’s Degree with 16 years of relevant industry experience; or a Bachelor’s Degree with at least 22 years of relevant experience is required.
- Relevant experience within Engineering, Physics, Math, or other disciplines related to quantitative biology/pharmacology with a strong emphasis on modelling and simulation of natural processes using mechanistic and/or a combination of mechanistic & empirical models.
- Excellent understanding of theory, principles, and statistical aspects of advanced mathematical modelling and simulation within physiology and pharmacology, e.g., hands-on experience with system biology, pharmacokinetics, or Physiologically Based Pharmacokinetics. Your ability to translate these tools into actionable insights is exceptional.
- Demonstrated expertise with ODEs, PDEs, ABMs, optimization, empirical approaches (statistics, ML) and ability to maintain state of the art know-how within QSP.
- Programming skills with modelling or analytical software (e.g., Matlab/SimBiology, Python, Julia, and/or R).
- Perceived as expert within the metabolic syndrome and/or liver-related diseases.
- Demonstrated strong ability to work in interdisciplinary teams, preferably with a focus to support and integrate in vitro and clinical pharmacology data into QSP models that describe the dynamic interactions between drug(s) and biological systems.
- Ability to operate with no or little supervision in a complex environment and disseminate knowledge by mentoring colleagues and/or supervising students.
- Demonstrated successful ability to engage, manage, and collaborate with external partners or service providers
- Previous experience with MPS and/or similar experimental setups is an advantage
- Keen to learn new skills and able to communicate with experts of other areas, effectively interact with colleagues with a variety of backgrounds, and have excellent written and oral communication skills in English.
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.
If you are interested in applying to Novo Nordisk and need special assistance or an accommodation to apply, please call us at 1-855-411-5290. This contact is for accommodation requests only and cannot be used to inquire about the status of applications.