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Job Post Details
Research Scientist, AIML & Drug Discovery - job post
4.04.0 out of 5 stars
Guntur, Andhra Pradesh•Hybrid work
Job details
Job type
- Contractual / Temporary
- Full-time
Location
Guntur, Andhra Pradesh•Hybrid work
Full job description
Job Description:
The Research Scientist, AIML & Drug Discovery Research Staff will apply artificial intelligence, machine learning, data science, bioinformatics, and computational tools to support AI-assisted drug discovery, healthcare analytics, predictive modeling, and research innovation.
Responsibilities:
The Research Scientist, AIML & Drug Discovery Research Staff will apply artificial intelligence, machine learning, data science, bioinformatics, and computational tools to support AI-assisted drug discovery, healthcare analytics, predictive modeling, and research innovation.
Responsibilities:
- Develop and support AI/ML models for drug discovery and healthcare research.
- Perform bioinformatics analysis using biological, genomic, proteomic, chemical, or clinical datasets.
- Support predictive modeling, data mining, visualization, and research analytics.
- Assist in virtual screening, molecular modeling, target identification, and compound prioritization when applicable.
- Collaborate with life sciences and pharmaceutical research teams to translate biological questions into data-driven projects.
- Prepare technical documentation, reports, presentations, posters, and publications.
- Maintain organized datasets, code repositories, version records, and reproducible workflows.
- Stay updated with emerging AI, bioinformatics, and computational drug discovery tools.
Requirements:
- B.Tech, M.Tech, B.Sc., M.Sc., M.Pharm, Biotechnology, Bioinformatics, AI/ML, Data Science, Computer Science, or related field.
- Experience with AI/ML, bioinformatics, computational biology, healthcare analytics, or drug discovery projects preferred.
Required Skills:
- Python, R, machine learning, data analysis, and visualization.
- Bioinformatics tools and biological databases.
- Predictive modeling and healthcare analytics.
- Molecular modeling or virtual screening tools preferred.
- Scientific documentation and interdisciplinary collaboration.
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