Statistical and computational modeling of soft matter
The PhD Curriculum in Statistical and computational modeling of soft matter is intended to form your researchers well-versed in developing and applying novel theoretical and computational techniques to tackle state-of-the-art problems in biological and soft condensed matter physics.
Applicants ought to have strong theoretical/computational backgrounds either in statistical mechanics or physical chemistry. Although applicants are clearly expected to be inclined and curious towards biologically-motivated problems no prior background in biology and biochemistry is assumed or required.
The appropriate expertise necessary to undertake a PhD scientific project (with typical duration of 3-4 years) will be initially provided from a series of courses that must be compulsorily attended in the first year. The didactical offer is, in fact, articulated over courses that are partly specific to this specific curriculum and partly mutated from other curricula namely:
Courses
1. Statistical mechanics (C. Micheletti)
The course reviews the fundamental basis of equilibrium statistical mechanics (ensembles, phase transitions, mean field theory, scaling theory, master equation, Metropolis and Monte Carlo sampling schemes)
2. Biomolecular Simulations and Structural Bioinformatics (P. Carloni, A. Magistrato, S. Raugei, C. Anselmi)
Molecular dynamics simulations; Quantum chemistry; Molecular docking; Homology modeling; Protein structure prediction; Computational Molecular Spectroscopy; Applications of molecular simulation to biological systems.
3. Biomolecular physics (P. Carloni)
Physical basis for structure and function of biomolecules
4. Advanced sampling techniques for numerical simulations (A. Laio)
The course provides an introduction to modern atomistic simulation techniques aimed at treating activated events and exploring complex potential energy surfaces arguments of the course will include: umbrella sampling and weighted histogram techniques, replica exchange transition path sampling; non-equilibrium thermodynamics techniques, such as Jarzynski method, metadynamics and Wang-Landau; nudged elastic band, eigenvalue following and the dimer method.
5. One course chosen among the fundamental teachings offered by the Condensed Matter sector: Many-body theory, Electronic structure, etc
6. Structural Biology (S. Onesti)
An overview of the various macromolecular structure determination methods, emphasising the strengths, limits and complementarities of the techniques. Theoretical and practical aspects of protein crystallography. Brief introduction to electron microscopy, NMR, SAXS, neutron and fiber diffraction. How to critically read a structural paper and how to use a PDB entry.
7. Probability and Stochastic Processes (M. Marsili)
8. In 2008 a new course will probably be offered on "Models and methods in biological physics" (A. De Simone and C. Micheletti)
RESEARCH LINes
After completion of the courses, students take on a research project under the supervision of a faculty member of the sector. The scope of the research typically falls within the active research lines of one or more members of the sectors. To provide concrete examples, the research lines that are being actively pursued at present regard:
- mesoscopic and atomistic modelling of the functional modes in enzymes.
- modelling of the mechanical (elastic) properties of biomolecules
- looping, knotting and entanglements in biopolymers.
- development of techniques for simulating rare events in biological systems.
- protein/protein interaction and protein folding.