Description

In this role, you will lead a dynamic team of data scientists, fostering collaboration between experimental and analytical scientists while advancing innovative data analytics methodologies in life sciences. Your work will directly impact research on disease models and contribute to groundbreaking publications.

Requirements

• •PhD in Computational Biology, Computer Science, Applied Mathematics, or related discipline
• •Expertise in AI/ML and statistical methods
• •Clear vision for integrating data modalities in spatial biology
• •Deep understanding of software engineering and open-source software platforms
• •Research track record with first-author publications in top-tier CS conferences and journals
• •Agility in adopting diverse analytical frameworks
• •Strong communication skills and collaboration across disciplines
• •Experience in leading project teams and/or mentoring students

Tasks

• •Establish and lead a team of data scientists
• •Integrate omics and imaging data sets in analytical workstreams
• •Partner with stakeholders to develop quantitative life science approaches
• •Bridge experimental scientists with computer scientists
• •Organize collaboration modes between Analytics team and experimentalists
• •Provide project consulting services and technology tutorials
• •Mentor researchers on analytical pipelines
• •Integrate research with Computational Biology Core and CS CoE
• •Recruit and guide the Analytics team based on developed guidelines
• •Build an agile data analytics team using AI/ML methodologies
• •Develop conduits for collaboration between experimental and analytical scientists
• •Assemble strategies for workforce development in life sciences
• •Create platforms for reproducible data analytics
• •Contribute to research on disease models and molecular processes
• •Implement computational biology practices in a biopharma organization
• •Disseminate scientific findings through publications and presentations