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Job id: 066967. Salary: £40,386 - £47,414 per annum, including London Weighting Allowance.

Posted: 09 May 2023. Closing date: 06 June 2023.

Business unit: Faculty of Life Sciences & Medicine. Department: Institute of Pharmaceutical Science.

Contact details: Cristina Legido-Quigley.

Location: Waterloo Campus. Category: Research.

Job description

We are looking for a highly skilled and self-motivated post-doctoral researcher with demonstrated expertise in modern bioinformatics analysis of high-dimensional data using programming languages such as R or Python. The successful candidate will be responsible for designing and implementing biostatistical and bioinformatic pipelines for analysing multiomic data sets, with a focus on identifying potential biomarkers and pathways associated with early neurodegenerative disease in clinical research. 

The candidate should also have experience with biomarker discovery methods and have expertise in data processing for mass spectrometry-based metabolomics, including annotation of small molecules. Experimental experience in this area is a plus.

The successful candidate must possess excellent project management skills and be able to work independently while consistently delivering high-quality results.

The candidate should also have excellent communication and interpersonal skills as the role involves coordinating with multiple international collaborators and stakeholders. The candidate will be part of a multidisciplinary team consisting of clinicians, analytical chemists, and biostatisticians.

In summary, we are seeking a highly motivated and skilled researcher with a strong background in bioinformatics and experience in biomarker discovery, data processing for metabolomics, project management, and excellent communication skills. The ultimate goal of this project is to identify potential pathways that may lead to the development of new treatments and prevention strategies for neurodegenerative diseases.

This post will be offered on a fixed-term contract for 17 months 

This is a full-time  post -

Key responsibilities

  • Conducting high-quality bioinformatics research.  
  • Processing and annotating metabolomics data from mass spectrometry. 
  • Setting up a pipeline to integrate and manage several multi-omics data sets with varying levels of information, quality, and privacy requirements. 
  • Applying modern bioinformatics analyses to large multi-omics data sets, including the identification of associations to outcomes, risk prediction, and causality inference. 
  • Interpreting, visualizing, and compiling results into manuscripts for publication. 
  • Demonstrating the ability to manage projects independently, consistently producing quality results that can be published. 
  • Coordinating with multiple international collaborators and stakeholders throughout the research project to ensure that research goals are achieved. 

The above list of responsibilities may not be exhaustive, and the post holder will be required to undertake such tasks and responsibilities as may reasonably be expected within the scope and grading of the post.  

Skills, knowledge, and experience 

The primary role of the post-doctoral research associate will be to develop and apply biostatistical and bioinformatic analysis to high dimensional omics data sets, including raw mass spectrometry data from metabolomics, thus the successful candidate is expected to have:

Essential criteria  

1.      A PhD in bioinformatics, computational biology, statistics or a related field 

2.      Demonstrated experience in using programming languages like R or Python for modern bioinformatic analysis of high dimensional data. 

3.      Experience with methods for biomarker discovery, preferably in clinical research 

4.      Experience in data processing for mass spectrometry-based metabolomics and annotation of small molecules 

5.      Proven ability to manage projects independently, consistently producing quality results and publications. 

6.      Excellent communication skills and the ability to work collaboratively in a multidisciplinary team 

Desirable criteria

1.      Experience with other types of omics data, such as genomics or proteomics 

2.      Hands-on experimental experience with mass spectrometry or other analytical techniques 

3.      Familiarity with machine learning algorithms and statistical models commonly used in bioinformatics analyses