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O firmie AbbVie

Misją AbbVie jest odkrywanie i dostarczanie innowacyjnych leków, które już dziś rozwiązują poważne problemy zdrowotne i stanowią odpowiedź na medyczne wyzwania jutra. Dążymy do wywarcia znaczącego wpływu na życie ludzi w kilku kluczowych obszarach terapeutycznych: immunologii, onkologii, neurobiologii, pielęgnacji oczu, wirusologii, zdrowia kobiet i gastroenterologii, a także w zakresie produktów i usług z portfolio Allergan Aesthetics. Aby uzyskać więcej informacji o AbbVie odwiedź nas na www.abbvie.com. Obserwuj @abbvie na portalach Twitter, Facebook, Instagram, YouTube i LinkedIn.

Senior Principal Scientist, Computational Oncology

Podstawowy Waukegan, Illinois Drugoplanowy Identyfikator oferty 2212215 Kategoria Research and Development Dział AbbVie

The Genomic Research Center Computational Oncology group (GRC-CO) at AbbVie is seeking a motivated and experienced computational biologist/bioinformatics scientist for a leadership position within a multi-disciplinary team focused on developing new therapies for the treatment of cancer. AbbVie’s GRC is a center of excellence for bioinformatics, functional genomics, human genetics, and genomic medicine. The GRC works across all R&D as well as other areas such as process sciences and corporate strategy.

This position will ideally be based at AbbVie’s headquarters located in North Chicago, IL, but remote and hybrid work options will be considered for experienced candidates.  The successful candidate will have the opportunity to work in a fast-paced and highly collaborative environment to contribute to oncology discovery and clinical development programs.  He/she will be responsible for formulating scientific questions into coherent analytical efforts, developing rigorous statistical modeling and bioinformatics methods, integrating large scale multi-modal datasets to derive quantitative biological insights, and communicating scientific findings to project teams. In addition, the candidate will contribute to presentations at scientific conferences, publications in peer-reviewed journals, new drug applications, and regulatory filings.

Key Responsibilities:

  • Lead a team to develop the translational bioinformatics strategy and set priorities
  • Partner with clinical development teams to address key project team questions related to genomic biomarker identification, companion diagnostic development, and communicate findings to internal and external stakeholders
  • Develop and apply statistical and computational tools for analysis of high dimensional data from oncology clinical trials, real world evidence datasets to enable biomarker strategy, drug combinations, understanding of MOA, disease subtypes, indication selection, patient stratification, etc.
  • Design and apply bioinformatics algorithms, unsupervised and supervised methods, univariate and multivariate regression analyses, machine learning and deep learning methods.
  • Collaborate with cross-functional teams to analyze and interpret complex large datasets and communicate findings to non-computational scientists and senior leaders.
  • Provide expertise and technical consultation for external collaborations/partnerships in academia and industry.

QUALIFICATIONS:

  • MS or PhD. Degree in bioinformatics, computational biology, statistics, mathematics, computer science, genomics, cancer biology, immunology, or a related field.
  • Minimum 10 (PhD) or 16 (MS) years of experience in a pharmaceutical, biotech or research organization with direct experience leading computational biology teams.
  • Experience with computational biology/bioinformatics in the field of clinical oncology development

Preferred:

  • Ability to be based at our North Chicago headquarters is preferred, but not required.
  • Extensive expertise in computational biology, bioinformatics, cancer genomics, and biomarker strategies. Good understanding of cancer biology, cancer signalling, immunology, and related subjects.
  • Proficient in either R or Python. Experience with any of the following programming languages also a plus: Java, C/C++, or Shell in a Linux environment.
  • Experienced with statistical analysis of genomic and transcriptomic data.
  • Expertise in predictive modeling, quantitative data analysis, and machine learning.
  • Develop and implement analysis workflow, software applications, and data warehouse to improve visualization, integration, and accessibility of complex genomics and clinical data.
  • Understand how to use and leverage containers for deploying standard pipelines (Docker, AWS Container, etc.).
  • Experiences with both preclinical and clinical development are highly valued.
  • Pro-active, collaborative scientist with outstanding presentation and communication skills that foster teamwork across a wide variety of functions and audiences.
  • A self-motivated individual with a strong work ethic capable of managing multiple objectives in parallel. At ease in a dynamic environment and quick to adapt to changing priorities.

AbbVie is an equal opportunity employer including disability/vets. It is AbbVie’s policy to employ qualified persons of the greatest ability without discrimination against any employee or applicant for employment because of race, color, religion, national origin, age, sex (including pregnancy), physical or mental disability, medical condition, genetic information, gender identity or expression, sexual orientation, marital status, status as a disabled veteran, recently separated veteran, Armed Forces service medal veteran or active duty wartime or campaign badge veteran or a person’s relationship or association with a protected veteran, including spouses and other family members, or any other protected group status. We will take affirmative action to employ and advance in employment qualified minorities, women, individuals with a disability, disabled veterans, recently separated veterans, Armed Forces service medal veterans or active-duty wartime or campaign badge veterans. The Affirmative Action Plan is available for viewing in the Human Resources office during regular business hours.


Zakres pracy: N/A
Podróż: No
Rodzaj pracy: Experienced
Harmonogram: Full-time
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