POSTGRADUATE PROGRAMS

Computational chemistry, which includes quantum chemistry, statistical mechanics, and molecular dynamics, uses computer simulations to study chemical phenomena. It predicts molecular structures, reaction pathways, and properties of materials with accuracy comparable to experimental methods.

M.Sc. Computational Chemistry at Amity University Punjab explores molecular simulations, quantum mechanics, and statistical methods to predict molecular structures, reactions, and material properties. It integrates chemistry with computer science and mathematics, preparing students for careers in drug discovery, materials science, and environmental research. Students of this course develop expertise in computational modelling, data analysis, and interdisciplinary collaboration. This is essential for advancing scientific understanding and innovation in diverse scientific domains.

Course Duration

• M.Sc. (Hons) - Computational Chemistry – 2 years

Eligibility Criteria

• M.Sc. (Hons) - Computational Chemistry – 2 years
  B.Sc. (H) Chemistry (min 50%) / B.Sc. (min 50%) with min 60% in Chemistry & 10+2 (min 60%) with PCM / PCB.

Fees:

M.Sc. (Hons) - Computational Chemistry: - First Year:1,00,000

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• M.Sc. (Hons) - Computational Chemistry – 2 years
• Biomolecular Simulation
• Intermolecular Potentials
• Reaction Dynamics
• Chemical Informatics
• Advanced Statistical Mechanics

Studying M.Sc. Computational Chemistry provides learners with advanced theoretical knowledge and practical skills essential for careers in scientific research, industry, and academia.

• Advanced Data Analysis: Develop skills in analysing complex datasets generated from simulations, interpreting results, and extracting meaningful insights.
• Computational Tools: Acquire proficiency in using software and algorithms to model molecular structures, predict properties, and simulate chemical reactions.
• Theoretical Foundations: Gain a deep understanding of quantum mechanics, molecular dynamics, statistical mechanics, and their applications to chemistry and materials science.
• Interdisciplinary Collaboration: Foster collaboration with experimental chemists, biologists, physicists, and computer scientists to integrate computational approaches with experimental findings.
• Problem-Solving Abilities: Learn to apply computational methods to solve challenging problems in drug discovery, materials design, and environmental chemistry.
• Research Skills: Conduct independent research projects, publish scientific papers, and present findings at conferences, preparing for doctoral studies or research-intensive careers.

Studying M.Sc. Computational Chemistry offers several key advantages:

• Interdisciplinary Knowledge: Bridge the gap between chemistry, physics, and computer science, developing a comprehensive understanding of theoretical principles and their practical applications.
• Industry-Relevant Expertise: Acquire skills highly valued in pharmaceuticals, materials science, environmental research, and biotechnology industries for drug discovery, materials design, and environmental impact assessments.
• Problem-Solving Abilities: Learn to tackle complex scientific challenges through computational modelling and simulation, providing insights and solutions not easily achievable through experimental methods alone.
• Research and Innovation: Engage in cutting-edge research, publish findings in scientific journals, and contribute to advancements in fields like molecular dynamics, quantum chemistry, and molecular modelling.
• Career Opportunities: Access diverse career paths in research institutes, academia, government agencies, and private sectors, with demand for computational chemists steadily increasing globally.

The faculty in Computational Chemistry comprises researchers with diverse backgrounds in chemistry, physics, and computer science. They possess advanced knowledge in theoretical modelling, quantum mechanics, molecular dynamics, and statistical mechanics. The key faculty roles include professors specializing in computational methods development, quantum chemistry, molecular modelling, and bioinformatics. They collaborate with experimental chemists, physicists, and biologists to advance research in drug discovery, materials science, and environmental chemistry.

Computational chemists are in high demand across industries for their ability to accelerate innovation, reduce costs, and provide insights into molecular behaviour that are difficult to achieve through only experimental methods.

• Academia and Research Institutes: Conducting fundamental research, developing computational models, and teaching advanced courses in computational chemistry.
• Biotechnology Industry: Simulating protein interactions, designing enzymes, and understanding biochemical pathways for biotechnological applications.
• Pharmaceutical Industry: Predicting drug-target interactions, optimizing drug design processes, and virtual screening of compounds for therapeutic efficacy.
• Environmental Research: Studying pollutant interactions, molecular dynamics of biomolecules, and developing sustainable chemical processes.
• Government and Regulatory Agencies: Contributing to drug safety assessments, environmental risk assessments, and policy development based on computational predictions.
• Consulting and Software Development: Providing expertise in computational modelling and simulation software development for various industries.
• Interdisciplinary Roles: Collaborating with experimental scientists in multidisciplinary teams to solve complex scientific challenges.

Notable professions after doing M.Sc. Computational Chemistry

• Computational Chemist
• Materials Scientist
• Environmental Chemist
• Biotechnologist
• Software Developer
• Research Scientist
• Academician

Programme Structure, Syllabi, Outline of Tests, and Course of Reading as follows

M.Sc. (Hons) - Computational Chemistry