Surface Engineering for Antifouling -
Coordinated Advanced Training (SEACOAT)
This is a temporary web page intended to support recruitment to the network. A more detailed web-site will be running soon
Positions available:
11 Early Stage Researcher (PhD) Fellowships
6 Experienced Researcher (post-doc) Fellowships
Applications are invited for Early Stage Researcher Fellowships (leading to a PhD) and Experienced Researcher Fellowships (post-docs) funded through a Marie Curie Initial Training Network. Most positions are due to start on March 1st 2010 or soon thereafter.
The SEACOAT Network:
The main research goal of the project is to improve understanding of biointerfacial processes involved in the colonisation of surfaces by marine fouling organisms. This will inform the future development of new, environmentally-benign materials and coatings for the practical control of marine biofouling.
Our principal objective is to discover which nano- and micro-scale physico-chemical properties of surfaces influence the adhesion of fouling organisms, through the use of surface engineering technologies to fabricate coatings that vary systematically in relevant surface properties, and length scales.
We will use advanced surface analytical methods to characterise test surfaces for relevant physico-chemical surface properties and how these change after immersion. Parallel adhesion bioassays using a range of representative marine organisms will test intrinsic antifouling properties of surfaces.
Fellows' individual projects will be integrated into one comprehensive research and training network which is strongly based on exchange and transfers between academia and industry. The network will also provide fellows with network-wide training activities (4 Advanced Training Courses, an international Workshop/symposium). All fellows are expected to collaborate with other Partners in the Consortium through secondments and visits.
http://www.biosciences.bham.ac.uk/SEACOAT
http://ec.europa.eu/euraxess/index_en.cfm?l1=1&l2=1&l3=1&idjob=31340927&CFID=487345&CFTOKEN=541be912248cacc8-D4B675CF-0583-2F81-7FD3591AFDA839A5
Coordinated Advanced Training (SEACOAT)
This is a temporary web page intended to support recruitment to the network. A more detailed web-site will be running soon
Positions available:
11 Early Stage Researcher (PhD) Fellowships
6 Experienced Researcher (post-doc) Fellowships
Applications are invited for Early Stage Researcher Fellowships (leading to a PhD) and Experienced Researcher Fellowships (post-docs) funded through a Marie Curie Initial Training Network. Most positions are due to start on March 1st 2010 or soon thereafter.
The SEACOAT Network:
The main research goal of the project is to improve understanding of biointerfacial processes involved in the colonisation of surfaces by marine fouling organisms. This will inform the future development of new, environmentally-benign materials and coatings for the practical control of marine biofouling.
Our principal objective is to discover which nano- and micro-scale physico-chemical properties of surfaces influence the adhesion of fouling organisms, through the use of surface engineering technologies to fabricate coatings that vary systematically in relevant surface properties, and length scales.
We will use advanced surface analytical methods to characterise test surfaces for relevant physico-chemical surface properties and how these change after immersion. Parallel adhesion bioassays using a range of representative marine organisms will test intrinsic antifouling properties of surfaces.
Fellows' individual projects will be integrated into one comprehensive research and training network which is strongly based on exchange and transfers between academia and industry. The network will also provide fellows with network-wide training activities (4 Advanced Training Courses, an international Workshop/symposium). All fellows are expected to collaborate with other Partners in the Consortium through secondments and visits.
http://www.biosciences.bham.ac.uk/SEACOAT
http://ec.europa.eu/euraxess/index_en.cfm?l1=1&l2=1&l3=1&idjob=31340927&CFID=487345&CFTOKEN=541be912248cacc8-D4B675CF-0583-2F81-7FD3591AFDA839A5
