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>
>--------
>BBSRC PhD Studentship
>
>Simulation-based analysis of the spatial distribution of macromolecular
>  complexes in mammalian cell nuclei.
>
>Department of Biological Sciences and
>Department of Mathematics, Imperial College London.
>
>The Department of Biological Sciences and Mathematics at Imperial College
>offer a three year PhD studentship funded by BBSRC.  The project involves
>the statistical analysis of confocal microscopy images of cell nuclei
>and nucleic components, with the goal of characterizing statistically the
>spatial patterns observed.  The biological goal of the project is to gain
>insight into cellular organisation.
>
>Project Details
>
>The principal aim of the project is to test the hypothesis that the
>complex spatial relationships occurring between functionally related
>macromolecular nuclear compartments correlates with the functional
>state of the cell, and that changes in these relationships can be used
>to predict cellular status.  A key goal is to develop a statistical
>toolkit with methods to quantitatively describe spatial distribution
>patterns of macromolecular compartments, access spatial relationships
>between functionally related complexes and design classification methods
>to investigate whether differences in cell nucleus spatial distribution
>exist in different cell types. Such developments represent significant
>methodological contributions in both applied probability/statistics
>and biological modelling and should lead to a mathematical definition
>for the normal steady state organisation of a 'virtual' nucleus.
>
>The student will be introduced to key skills in cell biology, immunological
>  methods, wide-field and confocal microscopy, image processing and the
>development of novel statistical methods and algorithms. Although the
>project involves limited "wet biology", the student will be provided
>with a working knowledge of cell biology to ensure that the student has a
>clear understanding of the current problems facing this area of research.
>The statistical skills developed over the course of the project will
>be of broad application, including training in technical probability
>skills, knowledge of current statistical analysis methodologies and
>statistical computing.  The student will develop wide ranging
>interdisciplinary expertise, essential for scientists hoping to bridge
>the gap between the life and physical sciences.
>
>Applicants must have at least an upper second class degree in Mathematics,
>Statistics, Biology or Computing.   Funding is only fully available
>to UK applicants.  Full details of the application process and funding can
>be obtained from Sandy Gray
>(<mailto:[log in to unmask]>[log in to unmask]).
>
>
>---------------------------
>
>MRC PhD Studentship
>
>Simulation-based analysis of the spatial distribution of
>macromolecular complexes in mammalian cell nuclei.
>
>Department of Biological Sciences and
>Department of Mathematics, Imperial College London.
>
>The Department of Biological Sciences and Mathematics at Imperial College
>offer a four year PhD studentship funded by MRC.  The project involves the
>statistical analysis of confocal microscopy images of cell nuclei and
>nucleic components, with the goal of characterizing statistically the
>spatial patterns observed.  The biological goal of the project is to gain
>insight into cellular organisation.
>
>Project Details
>The principal aim of the project is to test the hypothesis that the
>complex spatial relationships occurring between functionally related
>macromolecular nuclear compartments correlates with the functional
>state of the cell, and that changes in these relationships can be
>used to predict cellular status.  A key goal is to develop a
>statistical toolkit with methods to quantitatively describe spatial
>distribution patterns of macromolecular compartments, access spatial
>relationships between functionally related complexes and design
>classification methods to investigate whether differences in cell nucleus
>spatial distribution exist in different cell types. Such developments
>represent significant methodological contributions in both applied
>probability/statistics and biological modelling and should lead to a
>mathematical definition for the normal steady state organisation
>of a 'virtual' nucleus.
>
>The student will be introduced to key skills in cell biology,
>immunological methods, wide-field and confocal microscopy, image
>processing and the development of novel statistical methods
>and algorithms. Although the project involves limited "wet biology",
>the student will be provided with a working knowledge of cell biology
>to ensure that the student has a clear understanding of the current
>problems facing this area of research. The statistical skills
>developed over the course of the project will be of broad
>application, including training in technical probability skills,
>knowledge of current statistical analysis methodologies and
>statistical computing.  The student will develop wide ranging
>interdisciplinary expertise, essential for scientists hoping
>to bridge the gap between the life and physical sciences.
>
>Applicants must have at least an upper second class degree
>in Biolgical Sciences, Mathematics/Statistics, or Computing.
>  Funding is only fully available to UK applicants.
>
>Full details of the application process and funding can be
>obtained from Sandy Gray
>(<mailto:[log in to unmask]>[log in to unmask]).

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Dr. Andrew McMullan         Phone:0141-330 4852
Statistics Department       Email:[log in to unmask]
University of Glasgow
University Avenue
Glasgow
G12 8QQ
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