
IIT JAM 2027 syllabus: IIT Kharagpur has released the IIT JAM exam syllabus 2027 online. The syllabus is available for all seven papers. Candidates can check the IIT JAM syllabus PDF to know the important topics for exam preparation. Based on the exam syllabus, candidates can plan their preparation strategy. Candidates must follow the IIT JAM 2027 syllabus strictly. Preparation based on the exam syllabus will help in scoring good marks. Candidates must focus on building their conceptual knowledge. IIT JAM exam papers are concept-based. IIT Kharagpur will conduct the IIT JAM exam 2027 on February 14, 2027.
- IIT JAM 2027 Syllabus Download PDF
- IIT JAM Syllabus 2027 for Biotechnology (BL)
- IIT JAM Syllabus 2027 for Chemistry (CY)
- IIT JAM Syllabus 2027 for Mathematical Statistics (MS)
- IIT JAM Syllabus 2027 for Mathematics (MA)
- IIT JAM Syllabus 2027 for Economics (EN)
- IIT JAM Syllabus 2027 for Physics (PH)
- IIT JAM Syllabus 2027 for Geology (GG)
- IIT JAM 2027 Exam Pattern
- IIT JAM 2027 Preparation Tips
IIT JAM 2027 Syllabus Download PDF
Candidates can find the IIT JAM exam syllabus PDF 2027 below.
| Subject | Link |
| Biotechnology | IIT JAM 2027 Biotechnology Syllabus PDF |
| Chemistry | IIT JAM Chemistry Syllabus PDF |
| Mathematics | IIT JAM 2027 Mathematics Syllabus PDF |
| Mathematical Statistics | IIT JAM 2027 Mathematics Statistics Syllabus PDF |
| Physics | IIT JAM 2027 Physics Syllabus PDF |
| Economics | IIT JAM 2027 Economics Syllabus PDF |
| Geology | IIT JAM 2027 Geology Syllabus PDF |
IIT JAM Syllabus 2027 for Biotechnology (BL)
The JAM test paper for Biotechnology consists of four subjects - Biology, Chemistry, Mathematics, and Physics. Aspirants can go through the IIT JAM Biotechnology syllabus below:
IIT JAM 2027 Biology Syllabus
The standard of questions asked in IIT JAM 2027 for Biology subject is of 10+2+3 level. Topics that candidates need to study to perform well in the IIT JAM Biology section of the Biotechnology test paper are listed below.
| Subjects | Topics |
| General Biology |
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| Microbial, Plant and Animal Biotechnology |
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| Biotechniques |
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| Chemistry (10+2+3 level) |
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| Mathematics (10+2 level) |
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| Physics (10+2 level) |
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Also Read: IIT JAM Previous Years Question Papers: Download Last 5 Years JAM Subject Wise Question Paper PDF
IIT JAM Syllabus 2027 for Chemistry (CY)
The JAM test paper for Chemistry consists of three subjects, which are Physical Chemistry, Organic Chemistry, and Inorganic Chemistry. Aspirants can go through the detailed IIT JAM Chemistry syllabus 2027 below.
| Subjects | Topics |
| Basic Mathematical Concepts (10+2 Level) |
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| Physical Chemistry |
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| Organic Chemistry |
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| Inorganic Chemistry |
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Also Read: IIT JAM Eligibility Criteria 2025: Know Educational Qualification and Age Limit
IIT JAM Syllabus 2027 for Mathematical Statistics (MS)
The JAM test paper for Mathematical Statistics consists of two subjects which are Mathematics and Statistics. The weightage given to Mathematics is 40 per cent and Statistics is 60 per cent. Aspirants can go through the detailed IIT JAM Mathematical Statistics syllabus here. Find out the important topics for the Mathematical Statistics course below:
| Subjects | Topics |
| Section 1: Sequences and Series of Real Numbers | Sequences of real numbers, their convergence, and limits. Cauchy sequences and their convergence. Monotonic sequences and their limits. Limits of standard sequences. Limit superior and limit inferior of sequences. Infinite series and its convergence and divergence. Convergence of series with non-negative terms. Tests for convergence and divergence of a series. Comparison test, limit comparison test, D’Alembert’s ratio test, Cauchy’s nth root test, Cauchy’s condensation test, and integral test. Absolute convergence of series. Leibnitz’s test for the convergence of alternating series. Conditional convergence. Convergence of power series and radius of convergence. |
| Differential Calculus of one and two real variables, and Integral Calculus |
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| Matrices and Determinants | ℝn and ℂn as vector spaces over real field. Span of a set. Linear dependence and independence. Dimension and basis. Null space. Algebra of matrices. Standard matrices (Symmetric and Skew Symmetric matrices, Hermitian and Skew Hermitian matrices, Orthogonal and Unitary matrices, Idempotent and Nilpotent matrices). Definition, properties and applications of determinants. Evaluation of determinants using transformations. Determinant of product of matrices. Singular and non-singular matrices, and their properties. Trace of a matrix. Adjoint and inverse of a matrix, and related properties. Rank and nullity of a matrix, row-rank, column-rank, standard theorems on ranks, rank of the sum and the product of two matrices. Row reduction and echelon forms. Consistent and inconsistent systems of linear equations. Properties of solutions of system of linear equations. Use of determinants in solving the system of linear equations. Cramer’s rule. Characteristic roots and Characteristic vectors. Properties of characteristic roots and vectors. Cayley- Hamilton theorem. Quadratic forms, positive definite, positive semi-definite, negative definite, and negative semidefinite matrices, and their simple properties. |
| Descriptive Statistics and Probability |
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| Univariate Distributions | Definition of random variables. Cumulative distribution function (c.d.f.) of a random variable. Discrete and Continuous random variables. Probability mass function (p.m.f.) and Probability density function (p.d.f.) of a random variable. Distribution (c.d.f., p.m.f., p.d.f.) of a function of a random variable using transformation of variable and Jacobian method. Mathematical expectation and moments. Mean, Median, Mode, Variance, Standard deviation, Coefficient of variation, Quantiles, Quartiles, and measures of Skewness and Kurtosis of a probability distribution. Moment generating function (m.g.f.), its properties and uniqueness. Markov and Chebyshev inequalities, and their applications. Degenerate, Bernoulli, Binomial, Negative binomial, Geometric, Poisson, Hypergeometric, Uniform, Exponential, Double exponential, Gamma, Beta (of first and second type), Normal and Cauchy distributions, their properties, interrelations, and limiting (approximation) cases. |
| Multivariate Distributions | Definition of random vectors. Joint and marginal c.d.f.s of a random vector. Discrete and continuous type random vectors. Joint and marginal p.m.f., joint and marginal p.d.f.. Conditional c.d.f., conditional p.m.f. and conditional p.d.f. Independence of random variables. Distribution of functions of random vectors using transformation of variables and Jacobian method. Mathematical expectation of functions of random vectors. Joint moments, Covariance and Correlation. Joint moment generating function and its properties. Uniqueness of joint m.g.f. and its applications. Conditional moments, conditional expectations and conditional variance. Additive properties of Binomial, Poisson, Negative Binomial, Gamma and Normal Distributions using their m.g.f. Multinomial distribution as a generalization of binomial distribution and its properties (moments, correlation, marginal distributions, additive property). Bivariate normal distribution, its marginal and conditional distributions and related properties. |
| Limit Theorems | Convergence in probability, convergence in mean square, almost sure convergence, convergence in distribution, and their inter-relations. Weak law of large numbers, Strong law of large numbers, and Central Limit Theorem (i.i.d. and finite variance case) |
| Sampling Distributions | Definitions of random sample, parameter, and statistic. Sampling distribution of a statistic. Order Statistics: Definition and distribution of the rth order statistic (d.f. and p.d.f. for i.i.d. case for continuous distributions). Distribution (c.d.f., p.m.f., p.d.f.) of smallest and largest order statistics (i.i.d. case for discrete as well as continuous distributions). Central Chi-square distribution (𝜒2): Definition and derivation of p.d.f. of the central 𝜒2 distribution with n degrees of freedom (d.f.) using m.g.f. Properties of the central 𝜒2 distribution, additive property, and limiting form of the central 𝜒2 distribution. Central t - distribution: Definition and derivation of p.d.f. of the Central t -distribution with n d.f., Properties and limiting form of the central t -distribution. Central F -distribution: Definition and derivation of p.d.f. of the Central F - distribution with (m, n) d.f. Properties of the Central F-distribution, distribution of the reciprocal of the F-distribution. Relationship between t, F, and 𝜒2 distributions. |
| Estimation | Unbiasedness. Sufficiency of a statistic. Factorization theorem. Complete statistic. Consistency and relative efficiency of estimators. Uniformly Minimum variance unbiased estimator (UMVUE). Rao-Blackwell and Lehmann-Scheffe theorems and their applications. Cramer-Rao inequality and UMVUEs. Methods of Estimation: Method of moments, method of maximum likelihood, invariance of maximum likelihood estimators. Least squares estimation and its applications in simple linear regression models. Confidence intervals and confidence coefficient. Confidence intervals for the parameters of univariate normal, two independent normal, and exponential distributions. |
| Testing of Hypotheses | Null and alternative hypotheses (simple and composite), Type-I and Type-II errors. Critical region. Level of significance, size and power of a test, p-value. Most powerful critical regions and most powerful (MP) tests. Uniformly most powerful (UMP) tests. Neyman-Pearson Lemma (without proof) and its applications to construction of MP and UMP tests for parameter of one-parameter parametric families. Likelihood ratio tests for parameters of univariate normal distribution. |
| Nonparametric Methods | Tests of randomness based on total number of runs. Empirical distribution function. Kolmogorov-Smirnov one sample test. One and two sample sign tests. Mann-Whitney test. |
| Stochastic Processes |
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IIT JAM Syllabus 2027 for Mathematics (MA)
Aspirants can go through the detailed IIT JAM Mathematics syllabus here. The JAM test paper for Mathematics comprises of the below-mentioned topics:
| Subjects | Topics |
| Real Analysis |
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| Multivariable Calculus and Differential Equations |
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| Linear Algebra and Algebra |
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Also Read: IIT JAM question paper
IIT JAM Syllabus 2027 for Economics (EN)
Aspirants can go through the detailed IIT JAM Economics syllabus here. The IIT JAM test paper for Economics comprises of the below-mentioned topics:
| Subject | Topics |
| Mathematics for Economics |
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| Statistics for Economics |
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| Microeconomics |
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| Macroeconomics |
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| Indian Economy | Introduction and features: Changing structure of the Indian economy. Changing paradigms of Development Strategies and Economic Reforms. Poverty, Inequality, Inflation and Unemployment: Various concepts and estimates of poverty; Income Demographic Issues: Demographic trends, size and structure of population; Health and Education; Skill challenges and demographic dividends; Sustainable Development Goals—Targets for Greater Wellbeing and Better Human Capital. Perspectives in Agriculture, Industry and Services: Agricultural growth performance and food security, Industrial investment and growth, Service sector in India’s growth process. External Sector and Issues in Indian Public Finance: Foreign trade and trade policy; Foreign Exchange Reserves and exchange rate, Indian Union Budget, and fiscal policy. |
IIT JAM Syllabus 2027 for Physics (PH)
Aspirants can go through the detailed IIT JAM Physics syllabus below. The JAM test paper for Physics comprises of the below-mentioned topics:
| Subject | Topics |
| Mathematical Methods | Calculus of single and multiple variables, Partial derivatives, Jacobian, imperfect and perfect differentials, Taylor expansion, Fourier series, Vector algebra, Vector Calculus, Multiple integrals, Divergence theorem, Green’s theorem, Stokes’ theorem. First order equations and linear second-order differential equations with constant coefficients. Matrices and determinants, Complex numbers, Error analysis of Experimental Data: Significant digits and rounding of numbers, Types of errors, mean, median, standard deviation |
| Mechanics and General Properties of Matter | Newton’s laws of motion and applications, Velocity and acceleration in Cartesian, polar and cylindrical coordinate systems, uniformly rotating frame, centrifugal and Coriolis forces, Motion under a central force, Kepler’s laws, Gravitational Law and field, Conservative and nonconservative forces. System of particles, Center of mass, equation of motion of the CM, conservation of linear and angular momentum, conservation of energy, variable mass systems. Elastic and inelastic collisions. Rigid body motion, fixed axis rotations, rotation and translation, moments of Inertia and products of Inertia, parallel and perpendicular axes theorem, Principal moments and axes. Kinematics of moving fluids, equation of continuity, Euler’s equationDifferential equation for simple harmonic oscillator and its general solution. Superposition of two or more simple harmonic oscillators. Lissajous figures. Damped and forced oscillations, resonance. Wave equation, traveling and standing waves in one dimension. Energy density and energy transmission in waves. Group velocity and phase velocity. Sound waves in media. Doppler Effect. Fermat’s Principle. General theory of image formation. Interference of light, optical path retardation. Fraunhofer diffraction. Rayleigh criterion and resolving power. Diffraction gratings. Polarization: linear, circular and elliptic polarization. Double refraction and optical rotation. , Bernoulli’s theorem. |
| Oscillations, Waves and Optics | Differential equation for simple harmonic oscillator and its general solution. Superposition of two or more simple harmonic oscillators. Lissajous figures. Damped and forced oscillations, resonance. Wave equation, traveling and standing waves in one dimension. Energy density and energy transmission in waves. Group velocity and phase velocity. Sound waves in media. Doppler Effect. Fermat’s Principle. General theory of image formation. Interference of light, optical path retardation. Fraunhofer diffraction. Rayleigh criterion and resolving power. Diffraction gratings. Polarization: linear, circular and elliptic polarization. Double refraction and optical rotation. |
| Electricity and Magnetism | Coulomb’s law, Electric field and potential, Gauss’s law, Electrostatic boundary conditions, Solution of Laplace’s equation for simple cases – upto two dimensions. Conductors, capacitors, Linear dielectrics, dielectric polarization, volume and surface bound charges, electrostatic energy. Biot-Savart law, Ampere’s law, Faraday’s law of electromagnetic induction, Self and mutual inductance. Alternating currents. Simple DC and AC circuits with R, L and C components. Displacement current, Maxwell’s equations and plane electromagnetic waves, Poynting vector, Poynting’s theorem, Energy of Electromagnetic fields. Reflection and refraction at a dielectric interface, transmission and reflection coefficients (normal incidence only). Lorentz Force and motion of charged particles in electric and magnetic fields. |
| Kinetic Theory, Thermodynamics | Elements of Kinetic theory of gases. Velocity distribution and Equipartition of energy. Specific heat of Mono-, di- and tri-atomic gases. Ideal gas, van-der-Waals gas and equation of state. Mean free path. Laws of thermodynamics. Zeroth law and concept of thermal equilibrium. First law and its consequences. Isothermal and adiabatic processes. Reversible, irreversible and quasi-static processes. Second law and entropy. Carnot cycle. Maxwell’s thermodynamic relations and simple applications. Thermodynamic potentials and their applications. Phase transitions and Clausius-Clapeyron equation. Ideas of ensembles, Maxwell-Boltzmann, Fermi-Dirac and Bose-Einstein distributions. |
| Modern Physics | Inertial frames and Galilean invariance. Postulates of special relativity. Lorentz transformations. Length contraction, time dilation. Relativistic velocity addition theorem, mass energy equivalence. Blackbody radiation, photoelectric effect, Compton effect, Bohr’s atomic model, X-rays. Wave-particle duality, Uncertainty principle, the superposition principle, calculation of expectation values, Schrödinger equation and its solution for one, two and three dimensional boxes. Solution of Schrödinger equation for the one dimensional harmonic oscillator. Reflection and transmission at a step potential, Pauli exclusion principle. Structure of atomic nucleus, mass and binding energy. Radioactivity and its applications. Laws of radioactive decay. |
| Solid State Physics, Devices and Electronics | Crystal structure, Bravais lattices and basis. Miller indices. X-ray diffraction and Bragg's law; Intrinsic and extrinsic semiconductors, variation of resistivity with temperature. Fermi level. p-n junction diode, I-V characteristics, Zener diode and its applications, BJT: characteristics in CB, CE, CC modes. Single stage amplifier, two stage R-C coupled amplifiers. Simple Oscillators: Barkhausen condition, sinusoidal oscillators. OP-AMP and applications: Inverting and non-inverting amplifier. Boolean algebra: Binary number systems; conversion from one system to another system; binary addition and subtraction. Logic Gates AND, OR, NOT, NAND, NOR, exclusive OR; Truth tables; combination of gates; de Morgan’s theorem. |
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