Research Assistant

Location / Campus: South Kensington Campus - Hybrid

Job summary

The post is funded by the PREMIERE project to work on big data visualization with machine learning models.

The applications will be microfluidics (in particular droplet coalescence and droplet formation) and computational fluid dynamic simulations. The technologies used for modelling are based on Artificial Neural Networks.

Duties and responsibilities

• Characterisation of data visualization techniques to identify and develop suitable visualization demos using the Data Observatory at the Data Science Institute: https://www.youtube.com/watch?v=xBP72KLgQYM&t=10s
• To assist with the analysis of data
• To ensure the validity and reliability of data at all times
• To maintain accurate and complete records of all findings
• To assist with the writing of reports to research sponsors
• To present findings to colleagues
• To provide advice to other staff and students
• To assist with the publication of findings
• To attend relevant workshops and conferences as necessary
• To develop contacts within the College and the wider community
• To promote the reputation of the Group, the Institute and the College

Essential requirements

• A master degree (or equivalent) in Data Science, Machine Learning, AI or related disciplines
• Experience of data visualization
• Knowledge of basic research methods and statistical procedures
• Knowledge of programming languages such as Python
• Previous experience in a research laboratory environment

Further information

Candidates need to complete an online application on the Imperial jobs board.

Should you require any further details on the role please contact: Dr Rossella Arcucci – r.arcucci@imperial.ac.uk  

The College is currently trialling a Work Location Framework until early 2023. Hybrid working may be considered for this role and the role holder may be expected to work 60% or more of their time onsite, with 40% the minimum time spent onsite. The opportunity for hybrid working will be discussed at interview.

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