Position: Scientist, Computational Biology
Location: Bangalore, India
Cellworks is dedicated to advancing breakthroughs in modeling human biology, for the purpose of improving treatment of patients by changing the landscape of therapeutics. Cellworks strives to impact human disease and make a difference in patients’ lives, using a new wave of genome-based treatment decisions and tools for drug development. Join us as we make innovative advances with a new paradigm for bio-simulation based therapies, with a goal to help millions of patients worldwide
- Strong understanding of biological concepts and principles
- Proficient in Python or R; knowledge of SQL is a plus
- Critical thinking and problem-solving skills
Role and Responsibilities:
As a Scientist in Computational Biology at Cellworks, you will play a pivotal role in advancing our scientific understanding through computational methodologies. Your responsibilities will encompass a range of research-oriented tasks, methodology development, and collaboration with cross-functional teams to answer challenging scientific questions.
Research and Methodology Development:
- Conduct in-depth research to stay abreast of the latest advancements in computational biology and related fields.
- Develop and implement novel methodologies for the analysis of Genomic and Transcriptomic data and optimize existing pipelines for performance and scalability.
- Utilize data analysis techniques to extract meaningful insights from complex biological datasets.
- Apply machine learning algorithms to identify patterns and trends in large-scale biological data.
Innovation and Critical Thinking:
- Foster a culture of innovation by challenging existing norms and proposing creative solutions to scientific challenges.
- Actively contribute to brainstorming sessions and provide input on experimental design and data interpretation.
Bachelor's or Master's degree in Computational Biology, Bioinformatics, or a related field. Strong understanding of biological concepts and principles. Proficiency in programming languages such as Python or R; familiarity with SQL is a plus. Demonstrated experience in building and optimizing Genomic and Transcriptomic pipelines. Excellent critical thinking and problem-solving skills. Hands on experience in data analysis and machine learning is a plus.