Associate Professor

Amrita Vishwa Vidyapeetham; Kollam; On-site; INR 900,000 - 1,500,000; Full time

Job summary

Amrita Vishwa Vidyapeetham in Kollam invites applications for a faculty role in Biostatistics and AI-driven data science. You will teach UG, PG, and PhD courses, supervise theses, and lead AI/ML research across biostatistics and health datasets.

The position emphasizes collaboration with Amrita engineering schools, medical sciences, and international partners, with a focus on curriculum development and accreditation support.

Qualifications

• Strong background in biostatistics with theoretical and applied expertise.
• Experience in AI/ML applications for biostatistical or clinical data.
• Proficiency in Python, R, MATLAB, and SQL for modeling.
• Ability to collaborate across disciplines in health and biology.
• Excellent communication and leadership suited for academia.

Responsibilities

• Teaching UG, PG, and PhD courses in biostatistics and ML with labs.
• Lead AI/ML research in biostatistics or clinical data science; seek grants.
• Mentor PhD scholars and collaborate with Amrita institutes and partners.
• Contribute to curriculum development and institutional programs.

Skills

Biostatistics

ML Research

Programming (Python/R)

Interdisciplinary vision

Soft skills

Tools

Python

R

MATLAB

SQL

Job description

Key Responsibilities

1. Teaching: Deliver UG, PG, and Ph.D. courses in Biostatistics, Statistics, and ML; use coding labs and real datasets; supervise projects and theses.
2. Research: Lead AI/ML research in biostatistics, bioinformatics, public health, or clinical data science; secure SERB, ICMR, DBT, and DST grants; publish in Q1 journals and conferences.
3. Mentorship Collaboration: Guide Ph.D. scholars and faculty; collaborate with Amrita engineering schools, Amrita Institute of Medical Sciences, and global partners.
4. Institutional Development: Support curriculum, accreditation, administration, committees, and outreach.

Required Skills Competencies

• Statistical Expertise: Advanced proficiency in theoretical and applied biostatistics, multivariate analysis, longitudinal data analysis, survival analysis, and clinical trial design.
• AI Machine Learning: Deep practical and theoretical knowledge of machine learning algorithms (e. g. , Support Vector Machines, Random Forests, Gradient Boosting), deep learning architectures, and statistical learning theory.
• Programming Tools: Advanced proficiency in programming languages and tools commonly used for statistical modeling and AI (e. g. , Python, R, MATLAB, SQL).
• Interdisciplinary Vision: Ability to translate complex biological, health, or clinical datasets into actionable, productizable AI-driven insights.
• Soft Skills: Exceptional communication, collaborative ethos, and leadership qualities suited for a multi-disciplinary academic environment.