This programme offers students the opportunity to step into the shoes of a LifeArc team member and complete tasks that replicate the work that our biology research team does every day.
Who is it for?
Anyone keen to gain work experience or discover more about life sciences at LifeArc can complete the programme. It is particularly suited to first- and second-year undergraduates who may not be eligible for in-person work experience programmes.
What is the course outline?
This bespoke LifeArc programme has four modules on Biology at LifeArc. You can complete the modules at your own pace – it should take you approximately 4-6 hours in total. You’ll gain skills that could help with your onward studies and you’ll also receive a certificate that you can add to your CV and LinkedIn profile to stand out from the crowd.
What will you learn?
You’ll learn how to optimise experimental conditions, analyse data to determine optimal conditions, synthesise evidence and present your results.
1. Optimise experimental conditions
In this module, you’ll learn how to design a multiplexed experiment to optimise an in vitro neuronal differentiation protocol.
Practical skills include:
– Critical analysis
– Extracting relevant information
– Experimental controls
2. Analyse data to determine optimal conditions
In the second section, you’ll learn about visualising and performing statistical analysis of experimental data from an imaging assay using RStudio, which you can download for free.
Practical skills include:
– Data visualisation
– Statistical analysis
– Coding
– Reporting analysis & results
3. Synthesising evidence and collaboration
Here, you’ll see how to integrate the results of your data analysis with findings by your colleague and discuss a way forward.
Practical skills include:
– Data analysis
– Collaboration
– Communication
– Adaptability
4. Present your results
In the final module, we’ll guide you on how to present your and your colleague’s experimental results and provide suggestions for the way forward.
Practical skills include:
– Communication
– Collaboration
– Data analysis
– Presentation of data results
