AMD Scientific Assistant Physics Syllabus

NRSC Scientific Assistant SA3 Syllabus

As the AMD Scientific Assistant recruitment advt not shown full syllabus but  the applicant refer to this syllabus for AMD Scientific Assistant Physics exam 2020 which will conducted on 9th Feb 2020 in Hyderabad, Nagpur, Jaipur & Jamshedpur cities.

Mathematics
(1) Real Analysis
(2) Elementary Number Theory
(3) Groups and Rings
(4) Linear Algebra
(5) Ordinary and Partial Differential Equations
(6) Vector Calculus
(7) Solid Geometry

Physics
Mechanics – Fundamentals of Dynamics, Work & Energy, Collisions, Rotational Dynamics, Elasticity, Fluid Motion, Gravitation and Central Force Motion, Oscillation, Non-Inertial Systems, Special Theory of Relativity.
Electricity & Magnetism – Electric Field & Electric Potential, Dielectric properties of matter, Magnetic Field, Magnetic properties of matter, Electromagnetic Induction, Electrical Circuits, Network Theorems, Ballastic Galvanometer.
Waves & Optics – Superposition of Collinear Harmonic Oscillations, Superposition of two perpendicular Harmonic Oscillations, Wave motion, Velocity of waves, Superposition of two harmonic waves, Wave Optics, Interference, Interferometer, Diffraction, Fraunhofer Diffraction, Frensel Diffraction.
Thermal Physics – Introduction to Thermodynamics, Zeroth & First law of Thermodynamics, Second law of Thermodynamics, Entropy, Thermodynamic Potentials, Maxwell’s Thermodynamic relations, Kinetic Theory of Gases, Distribution of Velocities, Molecular Collisions.
Elements of Modern Physics
Statistical Mechanics & Electromagnetics – Classical Theory of Radiation, Quantum Theory of Radiation, Maxwell Equations.
Quantum Physics – Time dependent Schrodinger equation, Time independent Schrodinger equation.

Computer Science
(1) Mathematical Foundations
(2) Computer Organization
(3) Programming – Programming in C, Object oriented programming concepts including classes, Polymorphism, Inheritance, and Programming in C++, Java and Python
(4) Data Structures
(5) Design and Analysis of Algorithms – Algorithm complexity, Algorithms Design Techniques – Divide and Conquer, Greedy Method, Dynamic Programming, Backtracking, Branch and Bound, NP-Hard and NP-Complete Problems.
(6) Principles of Programming Languages – BNF, Variables, Data Types, Control Structures, Scope and Extent, Data Abstraction, Concurrency concepts, Exception Handling, Functional Programming and Logic Programming.
(7) Compiler Design
(8) Operation Systems
(9) Database Management Systems
(10) Computer Graphics
(11) Computer Networks
(12) Software Engineering
(13) Object oriented Analysis and Design
(14) Network Security
(15) Distributed Operating Systems