Brain and Artificial Intelligence (BAI)ĭepartment/Centre/Unit: Biochemistry (BC)īasic Qualification for Eligibility:Master’s or equivalent degree in any branch of Science or Bachelor’s degree in any branch of Medicine/ Engineering/ Technology/ Agriculture/ Veterinary Science/Pharmacy or Graduates of 4-year Bachelor of Science programmes.Īreas of Research:Protein structure and function Enzymology DNA-Protein Interactions Genomics and proteomics in different model systems Bioinformatics Systems Biology Plants and endophytic fungal secondary metabolites- their bioactivities and Biosynthesis Intracellular protein degradation Molecular chaperones Chaperone Mediated protein folding in the cell Mitochondrial Protein Transport Cellular immunology Infectious diseases Parasite biology and Host-pathogen interactions Chromosome Organization and Function Regulation of the Cell Cycle Eukaryotic gene expression Post-transcriptional gene control Cancer Genetics Genomic instability DNA repair and recombination Genetic diseases and Drug Discovery, Cell Division, Cytoskeleton biology, Synthetic Biology, Biomechanics and Actomyosin Molecular Plant Physiology and Land Plant Evolution Emerging virus infections, RNA sensing, Macromolecular signaling complex assembly.īasic Qualification for Eligibility:Master’s degree in Mathematical Sciences/ Physical Sciences or BE / B Tech or equivalent degree in any discipline or Graduates of 4-year Bachelor of Science programmes.Īreas of Research:Numerical Analysis Partial Differential Equations Controllability Nonlinear Dynamics and Chaos Probability Theory Random Matrix Theory and Random Analytic Functions Applied Probability and Stochastic Processes Stochastic Control Stochastic Dynamic Games Stochastic Geometry Interacting Particle Systems Time Series Analysis with Applications to Neuroscience Mathematical Finance Functional Analysis Harmonic Analysis Several Complex Variables Operator Theory Algebraic Topology Geometric Topology Combinatorial Topology Commutative Algebra Algebraic Geometry Differential Geometry Representation Theory Non-commutative Geometry Combinatorics Mathematical Physics Experimental Mathematics Modular Forms Analytic Number Theory.ĭepartment/Centre/Unit: Molecular Biophysics (MB). Biosystems Science and Engineering (BSSE).Instrumentation and Applied Physics (IN).Electrical Communication Engineering (EC).Solid State and Structural Chemistry (SS).Developmental Biology and Genetics (DBG).Analysis suggests that identifying a dominant hydropedological unit provides the most acceptable simplification of subsurface layering and that modified pedotransfer functions with steeper soil-water retention curves might adequately capture the influence of soil structure and hysteresis on hydrologic response in headwater catchments. Continuous simulations using pedotransfer functions that do not account for the influence of soil structure and hysteresis generally over-predicted runoff, leading to propagation of substantial water balance errors. For cases tested here, event-based simulations using simplified vertical heterogeneity did not capture the state-dependent anisotropy and complex combinations of runoff generation mechanisms resulting from permeability contrasts in layered hillslopes with complex topography. The viability of this latter method for capturing the seasonal transition from runoff-dominated to evapotranspiration-dominated regimes is also tested here. This paper tests the viability of two established and widely used hydrogeologic methods for simulating runoff and variably saturated flow through layered soils: (1) accounting for vertical heterogeneity by combining hydrostratigraphic units with contrasting hydraulic properties into homogeneous, anisotropic units and (2) use of established pedotransfer functions based on soil texture alone to estimate water retention and conductivity, without accounting for the influence of pedon structures and hysteresis. This study uses a distributed physics-based model to assess the influence of soil horizons and structure on effective parameterization. Often, only a single soil unit is employed, and soil-hydraulic properties are assigned based on textural classification, without evaluating the potential impact of these simplifications. Incorporating the influence of soil structure and horizons into parameterizations of distributed surface water/groundwater models remains a challenge.
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