INL Postgraduate School
The INL Postgraduate School is designed especially for Phd candidates pursuing their degree at INL, to equip them with essential skills beyond the lab, offering tailor-made training to enhance their academic and professional growth.
INL collaborates with higher education academic institutions to jointly co-supervise and mentor PhD candidates. While the research and development work is conducted at INL, the academic institution delivers the technical and degree-related coursework and is responsible for awarding the doctoral degree.
The INL Postgraduate School offers complementary and transversal training designed to enhance specific skills that support researchers in their future careers – whether in academia, industry, or entrepreneurship. These training activities help PhD candidates build a well-rounded professional profile, empowering them with a versatile skill set to succeed across diverse career paths.
Throughout their time at INL, PhD candidates receive personalised guidance to support their personal and professional development. This includes a structured series of workshops, masterclasses, and peer discussions tailored to each stage of their PhD journey. In the first year, the focus is on career planning, self-assessment, and navigating the early stages of the PhD. The second year emphasises time management, emotional intelligence, and networking skills. In the final year, candidates are prepared for the job market with targeted training on CV writing, interview techniques, and exploring both academic and non-academic career paths.
Topics
Communication
Data Management
Leadership
Teamwork
Ethics and Responsible Research
Entrepreneurship
Innovation
Career Management
Coursework Programme
The objective of this 30-hour Communication Course is to empower postgraduate students with the skills and techniques required for effective and impactful communication in academic and professional settings. Through two complementary modules, the course aims to enhance students’ abilities in scientific writing, oral communication, public speaking, and creative expression. By completing this course, participants will not only advance their technical communication skills but also gain a deeper understanding of the personal and social dimensions of impactful communication.
Module 1 – Communicating Science: Techniques for Writing and Speaking
This module focuses on improving the clarity, structure, and delivery of scientific communication.
Students will:
Develop skills in clarity, synthesis, audience engagement, and cohesive scientific writing.
Utilise tools and strategies to plan writing projects, establish goals, and maintain productive momentum.
Gain proficiency in providing and receiving constructive feedback.
Master techniques for designing, preparing, and delivering effective research presentations.
Improve their ability to create compelling data visualisations to enhance audience understanding.
Build confidence in public speaking through practical exercises.
Module 2: Stage Presence for Scientists.
This module leverages theatre techniques to strengthen interpersonal and presentation skills.
Students will:
Enhance critical thinking by analysing narratives, themes, and perspectives.
Build empathy and understanding by exploring diverse viewpoints.
Improve verbal and non-verbal communication for effective interactions.
Develop self-awareness, confidence, and resilience to overcome stage anxiety.
Foster creativity and imaginative thinking through theatrical exercises.
Strengthen collaboration and socialisation skills in group activities.
Boost self-confidence by achieving successful on-stage performances.
The objective of this 30-hour Data Course is to equip PhD students with essential skills in data management, analysis, visualisation, and artificial intelligence applications. Through four complementary modules, the course provides a comprehensive foundation for handling research data efficiently and effectively.
By completing this course, participants will develop technical proficiency in data handling, analysis, and presentation, equipping them with essential skills for research and professional applications.
Module 1: Research Data Management and FAIR Data Principles
This module introduces PhD students to key research data management (RDM) practices, fostering the adoption of FAIR data principles to enhance the credibility and reproducibility of scientific research. Students will:
Understand key RDM requirements and best practices.
Apply FAIR principles to data management.
Develop data management plans to support research compliance and efficiency.
Identify tools and resources that facilitate effective data sharing.Module 2: Data Analysis and Interpretation
This module provides students with fundamental skills in data analysis and interpretation, enabling them to derive meaningful insights from research data. Students will:
Understand the role and importance of data analysis in research.
Learn techniques for data collection, cleaning, and preparation.
Explore data through descriptive statistics and visualisation.
Apply basic statistical methods, including hypothesis testing and regression analysis.Module 3: Data Visualisation – Presenting Data with Impact
This module enhances students’ ability to communicate research findings effectively through data visualisation and storytelling. Students will:
Understand the influence of context on data interpretation.
Select appropriate visuals to convey messages clearly.
Use colours and design principles to highlight key insights.
Develop compelling narratives that transform data into meaningful stories.
Identify and avoid common pitfalls in data visualisation.
Apply storytelling techniques to create engaging presentations.Module 4: AI for Data – Applying Artificial Intelligence in Data Management, Analysis, and Visualisation
This module enhances students’ ability to communicate research findings effectively through data visualisation and storytelling. Students will:
Understand the influence of context on data interpretation.
Select appropriate visuals to convey messages clearly.
Use colours and design principles to highlight key insights.
Develop compelling narratives that transform data into meaningful stories.
Identify and avoid common pitfalls in data visualisation.
Apply storytelling techniques to create engaging presentations.This course will provide PhD candidates with a solid foundation in ethical research practices and responsible conduct. It covers key principles such as integrity, transparency, accountability, and respect in the research process. Participants will learn about INL’s Code of Conduct, as well as the role and support offered by the Research Ethics Committee (REC), including procedures for ethical review and guidance. Through case studies and interactive discussions, candidates will gain practical tools to navigate ethical challenges in their research and uphold the highest standards of scientific integrity.
This Innovation Course, under construction, is meant to provide a tailored training programme designed to introduce early-stage researchers to the world of innovation, entrepreneurship, and technology transfer. It aims to equip PhD candidates with the mindset, skills, and practical tools to think beyond the lab and explore how their research can lead to real-world applications. Through a series of engaging, hands-on modules, participants will:
Understand the role of innovation in scientific research and INL’s broader mission
Learn how to identify innovative potential in their work and explore pathways to protect, develop, and transfer technology
Get familiar with INL’s procedures and platforms, including invention disclosure, intellectual property (IP) protection, and spin-out support
Develop an entrepreneurial mindset and learn how to evaluate the societal and commercial impact of their research
Engage with internal experts and external innovation leaders through case studies, talks, and mentoring
This Leadership Course will be a 1-week course designed to equip PhD candidates with the essential leadership skills needed to thrive in research environments and beyond. Through interactive workshops fostering a collaborative and productive work environment, students will learn to leverage individual strengths, facilitate clear communication, and manage conflicts to achieve common goals. The course will also emphasise the development of a personal leadership style, preparing candidates to take on leadership roles in academia, industry, or entrepreneurial ventures.
Content:
Leadership concepts and styles, collaborative project management
Conflic resolution and negotiation
Mentoring and coaching
Building and leading interdisciplinary teams: recruitment, delegation, giving feedback, running effective meetings, etc.