Statistical/Machine Learning Data Analyst

University of Glassgow
April 16, 2024
Offerd Salary:£32,332 - £44,263
Working address:N/A
Contract Type:Open-ended
Working Time:Full time
Working type:N/A
Ref info:N/A
Statistical/Machine Learning Data Analyst

Job Purpose

The postholder will be responsible for performing analysis of large, complex, multi-platform data sets generated at the facility in support of world class research. This will entail research on appropriate statistical and machine- learning methodology in the areas of large scale omics data such as genomics, transcriptomics, proteomics/metabolomics and the integration of these, as well as outputs for functions such as protein analysis and cellular analysis. It will also involve writing software to implement developed algorithms, such that it can be used in a production environment.

The purpose of the job is also to provide specialist scientific advice and input to facility users to maximise the output of their datasets through novel analytical methods, and to disseminate that knowledge to staff and students through mentoring and training.

Main Duties and Responsibilities

1. Contribute to primary research objectives, supporting research projects to deliver optimal outcomes.

2. Work under supervision on assigned projects, providing high-end biological data research and statistical analysis to individual projects in next- generation sequencing (NGS), proteomics and metabolomics at the college of MVLS Shared Research Facilities (SRF).

3. Conduct research into the best methods to analyse SRF data, including their integration and display.

4. Contribute to the writing up of research and analyses performed for SRF clients, supporting high quality research publications.

5. Develop analytical workflows to extract meaning from various applications of NGS and proteomics/metabolomics projects and, in particular, their integration.

6. Optimize the presentation and dissemination of results.

7. Communicate with facility users and collaborators in order to understand the data analysis requirements and to explain both the techniques used and the results generated.

8. Maintain records and undertake general administration and clerical tasks supporting the projects.

9. Contribute to teaching activities performed by members of SRF, including demonstrating and supervising project students.

10. Share in the development of undergraduate or postgraduate students and less experienced members of the team by supervision, mentoring or training.

11. Develop and enhance own research profile and reputation, and those of the research group, SRF, and the University. This will include contributing to high quality publications in refereed journals, contributing to presentations at seminars and at national and international conferences, fostering and managing scientific collaborations, enhancing research impact, gathering indicators of esteem, engaging in personal and professional development, assisting in outreach activities

12. Manage workload activities as agreed with manager, balancing research and analyses for different SRF users.

For appointment at Grade 7:

13. Work independently and under supervision on assigned projects, providing high-end biological data research and statistical analysis to individual projects in next- generation sequencing (NGS), proteomics and metabolomics at the college of MVLS Shared Research Facilities (SRF).

14. Contribute to the research activities of SRF with the aim of developing an individual research programme. Promote future research by identifying potential funding sources.

15. Establish and maintain a track record of making a specialist contribution to publications of international quality and in high profile/quality refereed journals, enhancing research impact in terms of economical/societal benefit, gathering indicators of esteem.

16. Make a specialist contribution to grant funding applications.

17. Where relevant, to act as a co-supervisor for postgraduate research students.

Knowledge, qualifications, skills and experience



A1Scottish Credit and Qualification Framework level 10, (honours degree) in a relevant field.

OR Ability to demonstrate the competencies required to undertake the duties associated with this level of post having acquired the necessary knowledge and skills in a similar or number of different roles

For appointment at Grade 7:

A2 A PhD or equivalent qualification/experience in statistics, machine learning or data analysis.


B1 Demonstrable knowledge of biological concepts such as cells, genes, transcripts, proteins and metabolites.



C1 Excellent interpersonal, writing and presenting skills, and the ability to convey complex data and concepts clearly and concisely.

C2 Strong statistical skills especially in relation to applying statistical software.

C3 Ability to use initiative and judgement to resolve problems alone or as part of the group.

C4 Excellent interpersonal skills, including team working and fostering a collegiate approach.

C5 Ability to integrate into an active group involved in the generation, analysis and distribution of omics data.

C6 Ability to perform reporting duties in written and oral forms.

C7 Familiarity with integration of different data types.

C8 Excellent programming skills


D1 Demonstrable experience in the development of algorithms or software for statistical analysis of complex datasets or omics related applications

D2 Detailed knowledge and or/ hands-on experience of omics experimental methodology

D3 Ability to generate and follow own research programme in bioinformatics

D4 Proven track record in generating funding D5 Knowledge of NGS data analysis or proteomics/metabolomics data analysis. Willingness to extend knowledge to analyse all omics data that is generated at SRF

D6 Extensive theoretical and practical knowledge of biological data analysis and computing technologies



E1 Relevant experience in subject area

E2 Skill in complex or omics data analysis or equivalent, gained from previous experience across multiple projects.

For appointment at Grade 7:

E3 Demonstrable experience in a similar role, carrying out similar duties to a high standard.

E4 Experience of making a leading contribution in either research activities, or in equivalent roles in the workplace


F1 Experience in database development

F2 Experience of having programmed large software systems

F3 Experience of interpreting the requirements of others and generating high quality work to meet research objectives.

F4 Experience of working successfully in an interdisciplinary team

F5 Sufficient experience with Unix-like operating systems

F6 Sufficient experience in using Python

F7 Sufficient experience in using R

For appointment at Grade 7:

F8 Experience of co-authorship of peer-reviewed publications

Informal enquiries may be directed to Dr Ronan Daly, [email protected]

Terms and Conditions

Salary will be Grade 6/7, £32,332 - £44,263 / £39,347 - £44,263 per annum.

This post is full time and open ended.

As part of Team UofG you will be a member of a world changing, inclusive community, which values ambition, excellence, integrity and curiosity.

As a valued member of our team, you can expect:

1 A warm welcoming and engaging organisational culture, where your talents are developed and nurtured, and success is celebrated and shared.

2 An excellent employment package with generous terms and conditions including 41 days of leave for full time staff, pension - pensions handbook https: // www., benefits and discount packages.

3 A flexible approach to working.

4 A commitment to support your health and wellbeing, including a free 6-month UofG Sport membership for all new staff joining the University https: // www.

We believe that we can only reach our full potential through the talents of all. Equality, diversity and inclusion are at the heart of our values. Applications are particularly welcome from across our communities and in particular people from the Black, Asian and Minority Ethnic (BAME) community, and other protected characteristics who are under-represented within the University. Read more on how the University promotes and embeds all aspects of equality and diversity within our community https: // www.

We endorse the principles of Athena Swan https: // www. and hold bronze, silver and gold awards across the University.

We are investing in our organisation, and we will invest in you too. Please visit our website https: // www. for more information.

Vacancy Ref : 141029 Close Date : 16-Apr-2024 23:45

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