SASandoz
Investigator - Pathology
Warangal ₹5-7 LPA Posted 7 May 2025
FULL TIME
Machine Learning
Data Integration
Statistical Analysis
Bioinformatics
Job Description
- Use machine learning and statistical methods for analysis of spatial transcriptomics (e.g. Visium/Nanostring platforms) and spatial proteomics data (both internal and public data) from raw reads
- Compare and contrast spatial omics data sets with bulk RNASeq and single cell data
- Multimodal analysis of omics data with other modalities such as histopathology images, clinical biomarkers, etc.
- Support projects with data science expertise in diverse scientific fields such as gene and cell therapy, target discovery, genetics, drug safety, compound screening, etc.
- Innovate by transforming the way to solve a problem using Data Science & Artificial Intelligence
- Communicating regularly with stakeholders and assisting with answering their questions with the data and analytics
- Proactively evaluate the need of technology and novel scientific software, visualization tools and new approaches to computation to increase efficiency and quality of the Novartis data sciences approaches
- Independently identifies research articles and reproduce/apply methodology to Novartis business problems
- M.S. or PhD in Data Science, Computational Biology, Bioinformatics, or a related discipline
- Proficient in programming languages and data science workflows (e.g. Python, R, Git, UNIX command line, high-performance computing (HPC) clusters etc.)
- A minimum of 5 years of experience in analyzing large biological datasets (genomics, proteomics, and transcriptomics data analysis and data-integration) in a drug discovery/development or relevant academic setting
- Proven ability to implement exploratory data analysis and statistical inference in the context of scientific research
- A collaborative, team-focused mindset coupled with outstanding communication skills, and the ability to work in an agile environment
- Experience with using machine learning algorithms to extract insights from complex datasets
- Familiarity with the concepts of molecular biology, cell biology, genomics, biostatistics and toxicology