Job Description:
Lead the cardiovascular and metabolic disease area (CVM-DA) computational biology team. You will be responsible for driving shared global and local strategies to advance the understanding of CVM disease biology to enable target identification, drug development, and patient identification and stratification. Your responsibilities will include: leading the development of novel methods for the integration of multimodal profiling data to enable the discovery of novel biologic pathways and druggable targets in cardiovascular diseases as well as the identification of cardiovascular disease subpopulations; driving innovation and maintaining high quality reproducible research standards with a keen eye towards the identifying and disseminating actionable biological information; leading and participating on teams that bring together bench scientists, clinicians, software and network engineers, statisticians and other bioinformaticians to provide high quality analyses of genome scale experimental and clinical data; seeking and incorporating external datasets and external collaborations to further the CVM-DA strategic goals. You must have a proven ability to work collaboratively to provide high quality research results. Major Accountabilities: 1. Establish, communicate and drive integrated data analysis, dataset acquisition, and database architecture strategies that enable and shape the overall strategic vision of CVM-DA. 2. Develop and maintain integrated data analytic and data acquisition partnerships across NIBR Basic Research, Translational Medicine, and the Franchise partners to drive innovative discovery in alignment with CVM-DA strategic goals 3. Interface with key leaders and scientists across NIBR and Novartis, especially statistical and modeling groups, to address and resource analytical needs. 4. Independently identify external data sources in alignment with the overall CVM-DA portfolio at study, project, and disease area levels; identify and develop external partnerships and collaborators, academic and industrial, to aid in the mission of our groups. 5. Identify, develop, and implement innovative analytical methods that address drug discovery and development needs and gaps to increase productivity within the DA and in collaboration with internal or external groups. 6. Maintain the computational group by attracting and retaining the best talent, support the development of computational talent, and serve as a mentor to junior associates. Minimum requirements: - PhD and/or MD required in computational biology, bioinformatics, biostatistics, data science, cell or developmental biology, or a related field with 2+ years of management and leadership experience leading scientific analytical teams. - Fluent English communication skills (oral & written) - Leading, prioritizing resources and developing talent across a multidisciplinary team - Extensive experience in analytical methods as applied to large multi-modal biological datasets with an emphasis on machine learning approaches. - Deep hands-on understanding and analyzing pan-omic technologies. - Experience integrating different data modalities to gain biological insights; proven track record of high quality novel analytics and actionable biological insights - Experience with the analysis of next-generation sequencing data a must with associated expertise in R, Unix/Linux environments, and Python or other scripting language - Building partnerships and alliances with external parties. - Demonstrated ability to establish effective collaborative relationships with cross-functional scientific teams. - Excellent interpersonal and communications skills and ability to represent the group throughout the wider scientific community - Demonstrated organizational skills, aligning available resources to meet goals - Laboratory experience in molecular, cell, organismal biology strongly preferred
Additional Info:
EEO Statement: The Novartis Group of Companies are Equal Opportunity Employers and take pride in maintaining a diverse environment. We do not discriminate in recruitment, hiring, training, promotion or any other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, marital or veteran status, disability, or any other legally protected status.[Click Here to Access the Original Job Post]
Lead the cardiovascular and metabolic disease area (CVM-DA) computational biology team. You will be responsible for driving shared global and local strategies to advance the understanding of CVM disease biology to enable target identification, drug development, and patient identification and stratification. Your responsibilities will include: leading the development of novel methods for the integration of multimodal profiling data to enable the discovery of novel biologic pathways and druggable targets in cardiovascular diseases as well as the identification of cardiovascular disease subpopulations; driving innovation and maintaining high quality reproducible research standards with a keen eye towards the identifying and disseminating actionable biological information; leading and participating on teams that bring together bench scientists, clinicians, software and network engineers, statisticians and other bioinformaticians to provide high quality analyses of genome scale experimental and clinical data; seeking and incorporating external datasets and external collaborations to further the CVM-DA strategic goals. You must have a proven ability to work collaboratively to provide high quality research results. Major Accountabilities: 1. Establish, communicate and drive integrated data analysis, dataset acquisition, and database architecture strategies that enable and shape the overall strategic vision of CVM-DA. 2. Develop and maintain integrated data analytic and data acquisition partnerships across NIBR Basic Research, Translational Medicine, and the Franchise partners to drive innovative discovery in alignment with CVM-DA strategic goals 3. Interface with key leaders and scientists across NIBR and Novartis, especially statistical and modeling groups, to address and resource analytical needs. 4. Independently identify external data sources in alignment with the overall CVM-DA portfolio at study, project, and disease area levels; identify and develop external partnerships and collaborators, academic and industrial, to aid in the mission of our groups. 5. Identify, develop, and implement innovative analytical methods that address drug discovery and development needs and gaps to increase productivity within the DA and in collaboration with internal or external groups. 6. Maintain the computational group by attracting and retaining the best talent, support the development of computational talent, and serve as a mentor to junior associates. Minimum requirements: - PhD and/or MD required in computational biology, bioinformatics, biostatistics, data science, cell or developmental biology, or a related field with 2+ years of management and leadership experience leading scientific analytical teams. - Fluent English communication skills (oral & written) - Leading, prioritizing resources and developing talent across a multidisciplinary team - Extensive experience in analytical methods as applied to large multi-modal biological datasets with an emphasis on machine learning approaches. - Deep hands-on understanding and analyzing pan-omic technologies. - Experience integrating different data modalities to gain biological insights; proven track record of high quality novel analytics and actionable biological insights - Experience with the analysis of next-generation sequencing data a must with associated expertise in R, Unix/Linux environments, and Python or other scripting language - Building partnerships and alliances with external parties. - Demonstrated ability to establish effective collaborative relationships with cross-functional scientific teams. - Excellent interpersonal and communications skills and ability to represent the group throughout the wider scientific community - Demonstrated organizational skills, aligning available resources to meet goals - Laboratory experience in molecular, cell, organismal biology strongly preferred
Requeriments :
Skills :
- Cell Biology
- Lunix/Unix
- Machine Learning
- molecular biology
- Next Generation Sequencing
- Programing in Python
- Programming in R
Areas :
Additional Info:
EEO Statement: The Novartis Group of Companies are Equal Opportunity Employers and take pride in maintaining a diverse environment. We do not discriminate in recruitment, hiring, training, promotion or any other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, marital or veteran status, disability, or any other legally protected status.[Click Here to Access the Original Job Post]