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Topic: Post doc in metabolite identification (Read 346 times) previous topic - next topic

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Post doc in metabolite identification
Post Doctoral Research Associate (Structural Elucidation)
Imperial College London
Salary £36,070 - £43,350 per annum 

Applications are invited for an experienced chemist to support efforts in the identification of unknown metabolites (structure elucidation) from large scale metabolic epidemiology datasets.

The post holder will conduct de novo structure elucidation of unknown small molecules using Nuclear Magnetic Resonance (NMR) Spectroscopy, Mass Spectrometry (MS), and computational resources to interrogate the chemical structure of unknown compounds. With input from other members of the team, they will collate sufficient evidence to conclusively confirm metabolite structure, and implement new strategies to address chemical assignment problems. The primary source of unknowns will be a recently funded project examining the metabolic links between coronary artery disease and genetic variants.
 
The successful candidate should have a PhD or equivalent in Chemistry or related field, proven experience in the isolation and structure elucidation of metabolites using mass spectrometry, NMR, and other analytical methodologies and experience and knowledge of metabolic biotransformations and identification of metabolites. Experience in the preparation of scientific reports that document analytical results, and interpretation for the identification of biochemicals are desirable.
 
This full time position is offered for a fixed-term until 30 June 2018, and will be based primarily at the South Kensington campus with travel to the Hammersmith Hospital campus in White City when required.
 
For further information please contact Dr Tim Ebbels (t.ebbels@imperial.ac.uk) or visit the following link:
https://www4.ad.ic.ac.uk/OA_HTML/OA.jsp?page=/oracle/apps/irc/candidateSelfService/webui/VisVacDispPG&akRegionApplicationId=821&transactionid=1612084720&retainAM=Y&addBreadCrumb=S&p_svid=51247&p_spid=1825416&oapc=7&oas=dH-jupdNwYTKrsU6rO2GcA