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Activities offered across the university are mapped to a stage and strand of development.
The programme is underpinned by a focus on wellbeing, diversity and inclusion, knowledge in action and trans/interdisciplinarity. It is structured on six core strands of researcher development, you can see them below.
A set of minimum requirements is applicable to all research students starting from September 2022 onwards (and advisory for pre-September 2022 starters as well as our collaborative partner students), including:
- A minimum of 10 days (full time) or 5 days (part time) per year in line with the Research Concordat
- A researcher development plan (download from MyLearning)
- Engage with the specific aspects of development as a minimum requirement for each milestone of their studies
Use the filter to see available events and training that align with each strand.
For new research students (starting in September or January), we offer a kickstarting series that supports researchers across disciplines at the start of their research journey, providing them a forum where they can discuss anything they need as they get settled as researchers at Middlesex. It is particularly relevant to MPhil/PhD and MA/MSC by Research candidates but is open to all.
The workshops are designed to be followed as a series, with a focus on community and sharing of approaches – such that we all learn through dialogue and exchange.
Middlesex is an institutional partner of both CARMA and Instats.org, providing all Middlesex staff and students access to discounted research methods training as well as many free resources.
Instats seminars offer foundational and cutting-edge content delivered by leading experts. The live-streaming and on-demand seminars can be taken individually or as structured courses to provide researchers and faculty with the breadth and depth of knowledge they need. Through Instats you can find specialised methodologies training according to the specific needs of your research.
As a researcher at Middlesex you can undertake teaching within your Faculty and department. This is an opportunity to gain teaching experience, enhance your learning and your academic CV and develop your connections within academia.
In order to do so, you are required to complete the CAPE Short Course in Effective Teaching, which has been developed by the Centre for Academic Practice Enhancement (CAPE) and covers the fundamental principles of learning, teaching and assessment practice at Middlesex. The Course is designed to support researchers and colleagues for whom teaching at Middlesex is new, and is robustly aligned with the University's Strategic Plan 2031.
Completion of the Short Course is a mandatory requirement for doctoral students who have not previously taught at Middlesex.
Course Leader John Parkinson
Course Administrator Joanne Mullarkey
The below training is always available online on CARMA (MDX login); LinkedIn Learning (MDX login); Elsevier Academy (Open Access) (In addition, all Live sessions are available as recordings in the Research Degrees MDXplay channel).
Note: Many more sessions are available on CARMA, LinkedIn Learning and Elsevier Academy than listed here. In addition, you can access for free 1000+ methodological classes on Class Central.
Approaches & Methodologies | Subject/Sector Knowledge | The Digital Researcher |
Best Practices in Sourcing, Collecting and Managing Data [CARMA] | Advanced Interactions in Regression [CARMA] | Data Aggregation [CARMA] |
Mixing and Matching for Purporse [CARMA] | Advancing Science through Replication, Reproducibility, and Generalizabilty [CARMA] | Big Data Analytics [CARMA] |
A Framework for Methodological Rigorous Review Articles [CARMA] | Multiple Linear Regression [CARMA] | Big Data Concepts [CARMA] |
Mixed Mathods Workshop [CARMA] | Omitted variable bias [CARMA] | Introduction to R and table creation [CARMA] |
Triangulation and using multiple methods [CARMA] | Rigour and Trustworthiness in qualitative research [CARMA] | Creating Data Sets with Social Media [CARMA] |
Network analysis [CARMA] | Power analysis with regression models [CARMA] | Statistical analysis with big data [CARMA] |
Reflexivity in research methods [CARMA] | Introduction to multiple regression [CARMA] | 3-D visualization of data and models [CARMA] |
Grounded Theory and Discourse analysis [CARMA] | Neuroscience methods and organizational research [CARMA] | Learning Nvivo |
Robust and Reliable Research [CARMA] | Event Sampling Methods [CARMA] | SPSS Essential Training [LinkedIn Learning] |
Inductive Research Approaches [CARMA] | Panel Data [CARMA] | SurveyMonkey Essential Training [LinkedIn Learning] |
Cross-cultural research methods [CARMA] | Veryfing empirical research findings [CARMA] | Python Essential Training [LinkedIn Learning] |
How to integrate sex, gender, and intersectional analysis into research [Elsevier Academy] | Coding for discovery [CARMA] | Data Science Fundamentals [LinkedIn Learning] |
Video-based research methods [CARMA] | R Essential Training [LinkedIn Learning] | |
Artificial Intelligence Foundations [LinkedIn Learning] |
If you have any queries about these sessions please email researchdegrees@mdx.ac.uk
