Post 1 (Computational Biology and Bioinformatics)
Desirable Qualification: -
B.Sc./B.Tech with three years’ experience or
M.Sc./M.Techin Biotechnology/Bioinformatics from a recognized University with a minimum of 60% marks or equivalent CGPA
Essential Experience and Skills: -
1. Proficiency in Python and/or R for data analysis, statistical modeling, and machine learning
2. Demonstrated experience in multi-omics data analysis, including genomics, transcriptomics, proteomics, and/or metabolomics
3. Hands-on experience in machine learning and artificial intelligence applications for drug discovery, such as biomarker identification, target prioritization, and compound screening
4. Familiarity with biological databases, pathway and network analysis tools, and integrative statistical methods
5. Ability to integrate computational results with biological interpretation to support translational and drug discovery research
6. Strong problem-solving skills and ability to work independently or in a team along with good communication skills and scientific writing
Post 2 (Software Engineering and Data Science)
Desirable qualifications:
B.Tech./M.Tech. in Computer Science / IT / Data Science / AI / ML or M.Sc./M.Tech in Bioinformatics with 60% marks or equivalent CGPA from a recognized University.
Essential experience and skills:
1. Proficiency in Python-based frameworks, with working knowledge of (e.g., Django, Flask) or PHP-based frameworks (e.g., Laravel) for full-stack development, MySQL or Hadoop-based RDBMS for designing and managing large-scale datasets.
2. Proven experience to develop and maintain front-end (HTML, CSS) and back-end components (React, Vue.js or Node.js) of web portals handling multimodal datasets (genomics, text, images etc.).
3. Experience in developing and integrating Machine Learning, Large Language Models (LLMs), Generative AI, and Agentic AI systems, including prompt engineering, tool integration, and workflow orchestration.
4. Hands-on experience in model deployment, hosting, and API development for ML/AI and LLM-based applications.
5. Experience working with RESTful APIs, version control (Git) and cloud computing platforms (AWS, Azure, GCP, or equivalent).
6. Experience in managing scalable computational pipelines, databases, and interactive dashboards, particularly for scientific or healthcare applications.
7. Strong problem-solving skills and ability to work independently or in a team along with good communication skills and scientific writing.
