Please join us at the upcoming Royal Society of Chemistry Faraday Discussion:
Challenges in the Analysis of Complex Natural Mixtures Edinburgh, 13-15 May 2019 Oral abstract deadline: 27 July 2018
Most naturally occurring systems can be characterised as complex mixtures, such as biofluids, food or soil. Determination of their chemical composition is a highly challenging and is a key bottleneck in metabolomics. The techniques best positioned to tackle such mixtures experimentally include mass spectrometry, chromatography, NMR spectroscopy, or new alternative techniques, including combinations of the above methods. For the most part, people who work on the analysis of complex mixtures are driving the progress in exploiting new methodologies and their creative combinations. This Faraday Discussion will focus on four themes:
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.
Applications are invited for an experienced data analyst to work on processing and modelling metabolomic data. The post holder will join an existing collaboration, encompassing teams of data scientists, software engineers, epidemiologists, chemists and clinicians, tackling the problems of big data in metabolomics. The post will focus on developing statistical and machine learning models to integrate data from Nuclear Magnetic Resonance (NMR) spectroscopy and Mass Spectrometry, as well as electronic infrastructures to support the statistical modelling. The successful candidate will have a PhD in chemometrics, bioinformatics, biostatistics or similar area and will have strong coding skills in MATLAB or other scientific programming environment.
This full time position is offered for a fixed-term until 31 August 2017, and will be based at the South Kensington Campus in London. For further information please contact Dr Tim Ebbels (t.ebbels@imperial.ac.uk).
Hands-on LC-MS for Metabolic Phenotyping Date: 13 – 17 March 2017 Location: Imperial College London, South Kensington, London, UK Description: This week long course aims to cover how to perform a metabolic profiling experiment, from start to finish. It covers study design, sample preparation, the use of mass spectrometry for global profiling and targeted methodologies and data analysis. It combines lectures and tutorial sessions to ensure a thorough understanding of the theory and practical applications. Topics covered include:
Hands on Data Analysis for Metabolic Profiling Venue: Imperial College London, South Kensington, London, UK Early bird: £900 Standard: £1100
This 4 day course provides a comprehensive overview of data analysis for metabolic profiling studies with data acquired from NMR spectroscopy and Liquid Chromatography-Mass Spectrometry. It combines lectures and tutorial sessions to ensure a thorough understanding of the theory and practical applications.
Day 1: Introductory lectures and tutorials regarding the pre-processing of data acquired via NMR and LC-MS.
Day 2: Lectures and tutorials introducing exploratory chemometrics approaches, including PCA.
Day 3: Lectures and tutorials covering advanced chemometrics techniques including PLS and Orthogonal PLS.
Day 4: The next step - computational tools to aid metabolite identification and pathway analysis.
We are looking for two post-doctoral researchers in the field of bioinformatics/statistics applied to metabolomics and other omics data. Please see the attached adverts for more details or visit http://www3.imperial.ac.uk/employment.