Lecturer: Marco Thiel
Institution: Aberdeen
Hours Equivalent Credit: 33
Assessment: No assessment on this course
Note: This is a final year undergraduate course organised by the University of Aberdeen.
Course Summary:
This course shows you how to develop mathematical descriptions of phenomena. We use mathematical techniques to describe a large variety of “real-world” systems: spreading of infectious diseases, onset of war, opinion formation, social systems, reliability of a space craft, patterns on the fur of animals (morphogenesis), formation of galaxies, traffic jams and others. This course boosts your employability and teaches tools that are highly relevant for almost every researcher.
This is a sign-up / waiting list for anyone interested in the Hands On Writing course.
Due to limited places, we ask you to enrol into this course page, to allow us to collect a list of people interested in this course.
Names will be selected from this list to offer places on the course with priority being given to students in later years of their PhD, with names being drawn randomly thereafter.
Lecturer: Marcos Miralles Lopez
Institution: University of Glasgow
Delivery: Face to Face Hours Equivalent Credit: 9 (3 x 3 hour Labs)
Assessment: Continuous Assessment
Additional Resources
Material taught within the syllabus is intended to be supplemented by further reading. The recommended online tutorials are:
Official: http://root.cern.ch
Documentation: http://root.cern.ch/drupal/content/documentation
User's Guide: many PDFs by categories: http://root.cern.ch/drupal/content/users-guide
Tutorials: http://root.cern.ch/root/html/tutorials/
How To: http://root.cern.ch/drupal/content/howtos
Google a certain class to see its inheritance, members, examples, e.g. "ROOT TH1"
This course will provide a comprehensive introduction to the principles and practice of advanced data analysis, with particular focus on their application within the physical sciences and on the (rapidly growing) use of Bayesian Inference methods.
Over the past few decades Bayesian inference methods, as a powerful tool for analyzing data, have been growing ever more common across a diverse range of fields of physics. Bayesian inference provides a natural framework in which to address key quantitative questions, constrain the parameters of physical models and measure how well competing models can describe the available data. They also provide an objective and straightforward framework in which to incorporate prior information about those models, obtained e.g. from previous analyses or from theory. Moreover, recent advances in computational methods also offer simple algorithms in which to implement Bayesian methods – even with very large and complex data sets – on a standard desktop computer.
These lectures will give a comprehensive introduction to Bayesian inference methods. The lectures will include some practical exercises designed to introduce some useful codes and algorithms – as well as to showcase the vast array of online resources available to support the “virgin Bayesian” who seeks to apply these methods to their data.
Lecturer: Ik Siong Heng
Institution: Glasgow
Hours Equivalent Credit: 14 (10 online lectures and 7 tutorials)
Institution: Glasgow
Hours Equivalent Credit: 8 (4 lectures & 2x2hour tutorials)
Assessment: Assignment Problem
** This course is not offered in 2022/23. It may return in the future. **
Lecturer: Marialuisa Aliotta
Institution: Edinburgh
Hours Equivalent Credit: 15
Course Summary
The course is specifically tailored to PhD students in scientific disciplines. It will provide practical tools and strategies to help students understand key elements of good scientific writing. The course will cover the 5 steps of the writing process, from pre- writing to proofreading, and will focus on the structure and style of good academic writing. Topics covered will include: purpose and structure of different sections (Introduction, Methodology, Data analysis and Results, Discussion and Conclusions, Abstract); use of language and grammar (parallel sentences, appropriate tenses, sentence coordination); supporting materials (figures and tables, bibliography, appendices).
Lecturers: Cheryl Patrick
Institution: Edinburgh
Hours Equivalent Credit: 12
Assessment: Presentation
Course Summary
This course provides students with an opportunity to investigate current topics of interest relating to current Particle Physics research, and to present them. Presentations are recorded and participants receive staff and peer feedback.
