Program Full Name

DOCTOR OF PHILOSOPHY IN BIOPHYSICS

Program Level

Master's Degree

Duration of the Program

3 Years to 4 years

Examination Type

Year

Eligibility

Post-Graduation

Admission Process

Entrance Exam and Merit Based

Average Program Fee

Rs. 2 Lakh to Rs. 4 Lakh

Paper Code  

Subjects of Study

         1.                  

Physical Methods in Biology

         2.   

Information Processing and the brain                             

         3.               

Spectroscopy

         4.

Historical background of development of optics. Corpuscular is the theory of light, wave theory of light, lottery sambadElectromagnetic theory of light, Planck’s concept and modern theory of light. Electronic structures of atoms & molecules, theory of chemical bonding.

         5

Scattering of Light.

         6.                  

Hydrodynamic Methods

         7.               

Viscosity, Sedimentation equilibrium and velocity centrifugation, Density gradient method, applications.

        8.                   

Chromatography

        9.          

Partition and Absorption Chromatography, paper and thin layer chromatography, gel filtration, ion-exchange and affinity chromatography. GLC, HPLC and FPLC. Emerging trends in chromatography

       10.                  

Electrophoresis

       11.                  

Behaviour of biomacromolecules in electric fields, PAGE, Agarose Gel Electrophoresis, 2D Electrophoresis, Dialectrophoresis.

       12.                  

Radioactive Methods

       13.                  

Radioactive of isotopes, nature of radioactive decay, sample preparation and counting, G.M. and Scintillation counters. Precautions in radio isotope handling. Autoradiography and its biological applications.

        14.

Emerging topics in Biophysical methods

        15.                 

Electrical behaviours of the biological membrane.

        16.    

Introduction to Nervous System with a special reference to Sensory Receptors and Perception.

        17.                  .

Origin of the concept of the Computability, Turing Machine

        18.                 

Synaptic Transmission: Physicochemical Principles, Resting Potential, Action Potential, Membrane Theory of Action Potential, Hodgkin Huxley Model, Mathematical solutions of H-H equations.

      19.     

Models of Neurons: Artificial neurons, Physiological Neuronal Network versus Artificial Neural Network.

      20.                     

Mathematical tools to deal with Spiking Neurons.

      21.     

Neural Basis of Cognition: Principles of Learning and Memory, Cellular Mechanism of Learning and Memory, and Comparison with Machine Learning.

      22.   

Open discussions on the Interface of Artificial Neural Net and the Brain.