Location: University of Bordeaux, Allée de Saint-Hillaire, Bat B.14 - F33600 Pessac, France Tel. +33540006848 / Fax. +33540005200
Mail to: email@example.com
Period: 01/2012 – 06/2013 (18 months)
CNRS UMR 5248 CBMN (Chemistry and Biology of Membranes and Nano-objects) is a chemistry-biology laboratory which mission is to bring a fundamental knowledge of complex biological phenomena by analyzing them at several scales, from the molecule to the cell and to the organism. It is also strongly engaged in the development of analytical instrumentations, notably for bio-imaging purposes. Besides the fundamental aspects of research, the laboratory develops also applied studies for the characterization of molecular interfaces in their environment, from biochemical models (membranes, vesicles…) towards more complex biological samples.
The laboratory has the capacity to undertake this multiscale, multidisciplinary and multitechnical approach through its specialists recognized in the various fields, in chemistry, biology and physics.
We are looking for a postdoc for the CBMN laboratory, within the group “Spectroscopy and Imaging of Biosystems”. The person will primarily work on an infrared imaging system (Bruker HYPERION 3000 FTIR microscope equipped with FPA detector and ATR optics). The main responsibilities are:
- Take part to the development of ATR optics for in vitro FTIR imaging of living cells as well as biochemical models of membranes and vesicles,
- Take part to the coupling of different imaging approaches on the same biological samples, with possible utilization of ellipsometry imaging and Raman/AFM microscopy,
- Take part to the development of spectral data treatment methods for FTIR image reconstruction, potentially coupled to data from other imaging techniques.
The candidate should hold a Ph.D. or an equivalent degree in physics, physical-chemistry, bio-chemistry or a related discipline. Previous experience in FTIR spectro-imaging is mandatory.
Documented skills in developing complex experimental equipment, competency in data processing, good time organization proficiency, effective communication skills, and ability to work both unsupervised and in a team are highly desirable. The candidate must be fluent in English (written and spoken).
A 2-pages CV and two letters of recommendation should support the application.