AQMEN: Data Science Training

AQMEN are running the following training courses free of charge, on a first-come basis. Catering is provided and they are able to offer modest travel and/or accommodation bursaries to attend these events.

Data Wrangling – Organising and Enabling Data: 12th – 14th March 2019 London

This three-day workshop will provide a fast-track introduction for individuals wishing to learn how to work with data suitable for statistical analysis of business problems. Preparing and enabling data (data wrangling) is an essential aspect of undertaking data intensive statistical research. Data wrangling is highly time consuming and can be complex especially when dealing with messy data, which is often encountered in the business world.

Full details of the workshop and a link to register are available at

Predictive Data Analytics: 19th – 21st March 2019 Edinburgh

This three-day workshop will provide a fast-track introduction for researchers wishing to learn how to undertake statistical modelling using data from non-academic research domains. The workshop will introduce participants to fundamental concepts and approaches in statistical modelling and multivariate data analysis. There will be an emphasis on understanding outputs and interpreting results. These skills are critical for the successful analysis of complex data.

Full details of the workshop and a link to register are available at

Data Visualisation: 26th – 28th March 2019 London

Visualising data is emerging as a key component in effectively communicating research results and evidence. This three-day workshop will provide a comprehensive introduction for individuals wishing to learn how to design, produce and interpret data visualisations.

Full details of the workshop and a link to register are available at

CLOSER Workshop

CLOSER is running a workshop ‘Using multiple longitudinal studies for age-period-cohort investigation’ as follows:

Date & Time: Thursday 21 February 2019 09:30-16:00

Venue: Friends House, Euston Road, London NW1 2BJ

Longitudinal studies provide rich data for life course epidemiology (e.g. understanding some age-related process or its causes and consequences), but this power is magnified by working across multiple studies. In particular, with multiple cohorts (representative of the same population) born at different points in time, researchers can investigate how some age-related process or association has changed over time in response to shifts in the behavioural, nutritional, and political etc. environments.

This workshop will focus on the use of multiple longitudinal studies for age-period-cohort investigation.

This event is aimed at PhD students and early-career researchers, however everyone is welcome to attend.

Speakers include: Dr Will Johnson, Dr Silvia Costa, Dr Tom Norris and Liina Mansukoski (Loughborough University), Dr Andrew Bell (University of Sheffield), Dr Alice Goisis (LSE), and Dr Anamaria Braelian (King’s College London)

Click here to view the programme

Click here to book your place on this free workshop

Is it just me? Discussing mental health and the PhD experience

Date: 30 January 2019

Time: 16:00 – 18:00

Location: Mason Lecture Theatre in Bancroft Building (no. 31 on the map), Queen Mary University of London, Mile End.

This event aims to raise awareness of mental health issues among PhD students and will consist of talks by invited academics who have worked on the topic, a panel discussion and questions from audience members. A reception will follow at the Bancroft building foyer from 18:00.

For more information, including abstracts and bios, and to register, please visit:

Registration is free and open to everyone.

NCRM Courses for 2019

The National Centre for Research Methods are offering new training courses for 2019. We will be announcing more courses as they are finalised, but here are the confirmed courses for 2019 so far:

Quant for qual researchers | 8-10 January | Cardiff

Longitudinal structural equation modelling with R | 31 January – 1 February | Southampton

Understanding small areas: spatial analysis of population & neighbourhood data | 7-8 February | Manchester

Accessing data quality and disclosure risk in numeric data | 20 February | London

How to write your methodology chapter | 26 February | Southampton

Introduction to GIS | 4-7 March | Southampton

Introduction to latent class analysis | 14-15 March | Manchester

Introduction to spatial data and using R as a GIS | 27 March | Southampton

Spatial interaction modelling | 28-29 March | London

Introduction to data linkage and analysing linked data | 1-2 April | London

Using creative research methods | 3 April | Cardiff

Interpretive political science | 20-22 May | Southampton

Introduction to spatial data and using R as a GIS | 23 May | London

Drawing, multimodality & interaction analytics | 28 November | London

As a rule, our courses cost £30 a day for UK/EU students and £60 a day for UK/EU academics, researchers or public service staff. More details on specific course costs are available by clicking the above links.

For more information about our training courses, please visit:

PhD Internship Opportunity at the Royal Institution

The Royal Institution (Ri) is looking for an intern to start in mid to late January 2019 to assist the Ri team with preparation for the Big Bang Fair in March 2019. This placement will involve working with the Ri during the peak period for science engagement with schools in the UK, the period around National Science Week. Due to the focus of the internship, the dates are not flexible.

The role is based in Central London (with the requirement to travel to Birmingham for the Big Bang Fair) so students will be expected to base themselves within or near to London for the period of the placement.

The closing date for receipt of applications is midnight on Tuesday 4th December 2018 and interviews are scheduled to be held during week commencing 17th December 2018.

Please find the job description for the internship here: Big Bang Fair intern JD

More information about the Ri’s internship programme and details on individual placements, timeframes and how to apply can be found here: