Senior Scientist II or Principal Research Scientist I, Immunology
AbbVie
US
Job highlights
Qualification
PhD. Degree in bioinformatics, statistics, mathematics, computer science, computational biology, genomics or a related field with 4-6 years of experience or Master’s degree with typically 10-12 years of experience. A minimum of 3 years of relevant experience working on omics data analysis. Hand on experience with using generative, discriminative, and contrastive machine learning methods to analyze multi-omics datasets. Strong understanding of theoretical foundations of machine learning methods. Experience in the use of machine learning methods for NLP and text analysis. Experience in the process and analysis of real world data. Highly proficient with statistical and programing languages (R, Python), Unix/Linux/cloud environment, and SQL and noSQL database query languages. Position will be filled at level commensurate with extent of education, experience, and accomplishment
Responsibility
This position will be based in Cambridge, Massachusetts, and the candidate will work closely with computational biologists across the network and be embedded in research project teams in immunology discovery and precision medicine to analyze multi-omic datasets to derive insights into immunological diseases, identify novel therapeutic targets and biomarkers specific to patient cohorts and AbbVie pipeline drugs. The successful applicant will develop new machine learning methods and practices to address key project team questions related to forward/reverse translation, genomic biomarker identification, companion diagnostic development and mechanistic characterization, and communicate findings to internal and external stakeholders. In addition, the candidate will contribute to presentations at scientific conferences and publications of translational findings in peer reviewed journals, new drug applications and regulatory filings. Evaluate, develop and apply machine learning methods for integration of preclinical and clinical multi-omics data. Use machine learning methods for knowledge extraction from unstructured data to perform data harmonization. Develop graph convolution models to various use cases based on internal heterogenous networks. Integrate real world data with other omics data to support target identification and validation. Communicate analytical approach and results verbally and in writing for scientific and technical audiences. Provide expertise and technical consultation for external collaborations/partnerships in academia and industry
Job Description
Description
The Genomic Research Center (GRC) Immunology Computational Biology group at AbbVie is seeking a highly motivated computational biologist to play an integral role in a multi-disciplinary team focused on developing new therapies for the treatment and cure of immunological diseases. AbbVie’s GRC is a center of excellence for bioinformatics, functional genomics, human genetics and pharmacogenomics. The GRC works across all R&D including discovery and clinical development, and multiple areas such as process sciences, search and evaluation and corporate strategy. This position will be based in Cambridge, Massachusetts, and the candidate will work closely with computational biologists across the network and be embedded in research project teams in immunology discovery and precision medicine to analyze multi-omic datasets to derive insights into immunological diseases, identify novel therapeutic targets and biomarkers specific to patient cohorts and AbbVie pipeline drugs. The successful applicant will develop new machine learning methods and practices to address key project team questions related to forward/reverse translation, genomic biomarker identification, companion diagnostic development and mechanistic characterization, and communicate findings to internal and external stakeholders. In addition, the candidate will contribute to presentations at scientific conferences and publications of translational findings in peer reviewed journals, new drug applications and regulatory filings. Key Responsibilities: • Evaluate, develop and apply machine learning methods for integration of preclinical and clinical multi-omics data • Use machine learning methods for knowledge extraction from unstructured data to perform data harmonization • Develop graph convolution models to various use cases based on internal heterogenous networks • Integrate real world data with other omics data to support target identification and validation • Communicate analytical approach and results verbally and in writing for scientific and technical audiences • Provide expertise and technical consultation for external collaborations/partnerships in academia and industry Qualifications: • PhD. Degree in bioinformatics, statistics, mathematics, computer science, computational biology, genomics or a related field with 4-6 years of experience or Master’s degree with typically 10-12 years of experience • A minimum of 3 years of relevant experience working on omics data analysis • Hand on experience with using generative, discriminative, and contrastive machine learning methods to analyze multi-omics datasets • Strong understanding of theoretical foundations of machine learning methods • Experience in the use of machine learning methods for NLP and text analysis • Experience in the process and analysis of real world data • Highly proficient with statistical and programing languages (R, Python), Unix/Linux/cloud environment, and SQL and noSQL database query languages Preferred Qualifications: • Expertise in computational biology, biostatistics and biomarker strategies • Good understanding of immunology disease biology • 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 • Ability to work in a multiple-task, fast-paced, highly collaborative and dynamic work environment • Proactive scientist with outstanding presentation and communication skills that foster collaboration and teamwork • A collaborative and self-motivated individual with a strong work ethic, ability to work in a dynamic environment and able to manage multiple objectives in parallel and adapt to changing priorities Position will be filled at level commensurate with extent of education, experience, and accomplishment AbbVie is committed to operating with integrity, driving innovation, transforming lives, serving our community, and embracing diversity and inclusion. 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 protected veteran, or any other legally protected group status. Tagged as: Life Sciences