Sr. Computational Biology Scientist - Target Discovery

About the Department                                                                                                                                             

You will be joining the US Target Discovery team within the Novo Nordisk Artificial Intelligence and Digital Research (AIDR) Computational Biology department. AIDR Computational Biology is a global department with colleagues in China, Denmark, the United Kingdom and the United States. Our scientists have significant expertise across a diverse set of disciplines in computational biology, bioinformatics, and machine learning, including multi-omic data analysis, functional genomics, systems biology and biomarker analysis. The focus of the US Target Discovery team is drug target identification through the analysis of high throughput functional genomics, transcriptomics and cell imaging data. The use of cutting-edge machine learning techniques to identify novel drug targets in our core disease areas is a key objective for AIDR as we seek to strengthen the Novo Nordisk drug discovery portfolio and deliver new medicines for patients.

The AIDR team sits within the wider Digital Science & Innovation (DSI) organi-sation. DSI is supporting the digital journey across all our therapy areas in No-vo Nordisk Research and Early Discovery (R&ED). In DSI, we work in multidisci-plinary 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 auto-mate our labs and processes, and we focus on developing and retaining top talent.

 

The Position

As Senior Scientist I you will be responsible for using computational analysis and machine learning to discover and validate novel drug targets in Novo Nordisk’s key disease areas, including diabetes, obesity and cardiovascular disease.

 

Relationships

The Senior Scientist I reports to the head of Computational Biology Target Discovery US. The role will work closely with the Target Discovery Engine (TDE) team within Global Drug Discovery as well as colleagues across the global Computational Biology area including in the United Kingdom, Denmark and China.

 

Essential Functions

• Scientific work:
  • Perform computational biology data analysis, particularly of Novo Nordisk Target Discovery Engine data, to identify novel drug targets in diabetes, obesity and cardiovascular disease.
  • Develop relationships with key stakeholders in Global Drug Discovery, especially the Target Discovery Engine (TDE) in US, UK and CHN, to en-sure delivery of TDE objectives.
  • Input into the Target Discovery US CB scientific strategy and operations.
  • Mentor and guide junior members of the Target Discovery US CB team
• Collaborative teamwork
  • Actively participates in cross-functional teams to develop AI and ML solutions
  • Actively participates in virtual global team meetings regularly
  • Achieves business goals, shares learnings, knowledge and skills and promotes cross-functional teamwork
  • Raise the level of competency in the team by seeking and sharing domain knowledge in the area of Data Science, as well as Novo Nordisk’s therapy areas
  • Demonstrates aptitude for establishing and maintaining relationships with colleagues both locally and globally
  • Occasionally collaborate with external partners

 

Physical Requirements

Up to10% overnight travel required; potentially including international 

 

Qualifications

• Master’s degree required; PhD is preferred.  Degree within a computational biology discipline, such as bioinformatics or ge-nomics preferred
• Master’s Degree with 3+ years’ relevant experience, or PhD with little to no years’ relevant experience can be considered
• Relevant experience includes some combination of :
  • Experience of applying computational biology and machine learn-ing to target discovery through genetics or functional genomics.
  • Experience analysing diverse omics data including one or more of RNASeq, scRNASeq, CRISPR gene editing & screening.
  • Experience working in Python or R to curate and analyze data.
  • Experience in working in multidisciplinary teams and working environments.
  • Ability to perform in-depth data analysis and present results and conclusions to diverse project teams.
  • Excellent written and oral communication skills
  • Detail oriented with strong presentation and documentation skills.
• Preferred experience includes:
  • Experience analysing in vitro high throughput imaging data with machine learning.
  • Experience working with cl