STFC Data Intensive, Artificial Intelligence and Machine Learning Summer School 2019

Sunday 21st July (16:00) to Friday 26th July (17:00)

The Conference Centre, University of Sussex campus

AIM: to provide students with additional skills to support academic research projects, industry placements and possible career paths into industry.

Small group of students on last day of Summer School

Registration for the Summer School is now closed.

Any queries should be directed to Louise Winters, Project Manager for the Summer School.


Click here to see more photographs of our fantastic students and amazing contributors to the event.


We gratefully acknolwedge the following organisations for their support of the Summer School:

 Logo of the Science and Technology Facilities Council . Cambridge Spark Logo  EduKate Logo  Ripjarlogo


Summer School Programme

The programme for the Summer School is now online and registered attendees have indicated their workshop preferences. 

View the timetable here.

The programme is divided into the following activities:

Hands on workshops: the majority of your time will be spent in small group, interactive workshops. You will choose 1 course (from a choice of up to 5) to study each day which will total approximately 4.5 hours of teaching time during the day. So each attendee will take 5 courses during the course of the School.

Plenary sessions: From 16:00 - 17:30 each day there will be a plenary session for all attendees. These will include lectures from Astronomy, Particle Physics, Machine Learning and on Data Science in industry.

Evening activities: Social and networking events are scheduled including a Welcome & Icebreaker evening, games evenings, an industry networking event and the conference dinner.

Topics & Speakers

List of possible topics for Summer School workshops (final topics are yet to be confirmed):

AI and Machine Learning:
  • Data Compression and feature identification (e.g. PCA, ICA, NMF, auto encoders etc)
  • Deep learning (inc. CNN & GAN)
  • Bayesian Hierarchical modelling (e.g. with PyStan)
  • Fairness and interpretability
  • Boltzmann Machines
  • Clustering tools (e.g. Gaussian Mixtures, Self-Organising Maps etc.)
  • Specific Supervised Classification tools (e.g. SVM, Random Forest, Naive Bayes, Logistic Regression etc.)
High Performance / High Throughput Computing
  • Cloud Computing (e.g. AWS)
  • GPU Programming
  • Statistics and Modelling

Statistics and Modelling
  • Advanced Statistics
  • Approximate Bayesian Methods (e.g. Variational Bayes)
  • Evidence and Model Selection
  • "Traditional" data analysis and statistical methods (e.g. Multi-variate analysis, time-series, survival analysis)
  • Sampling Methods (e.g. Hamiltonian MC, nested sampling, etc.)
  • Gaussian Processes (GP) for regression and classification
  • Natural Language Processing (NLP)
General Programming:
  • Tensorflow / Keras / Py Torch
  • Containers (e.g. Docker, Singularity)
  • Advanced Git, GitHub
  • Julia
  • Probabilistic Programming Language (e.g. Stan)
  • Pandas/Numpy
  • Scikit-learn
Big Data Tools
  • Apache Spark for Astronomy
  • SQL
  • Apache Spark
Miscellaneous Data topics
  • Bias and Ethical Machine Learning]
  • Data Wrangling]
  • Data Visualisation using R]

The University of Sussex is located in Falmer which is a short bus or train ride away from Brighton, an hour from London and 30 minutes away from Gatwick international airport. (directions to the University).

Further local information is available at Visit Brighton (webpage image supplied by VisitBrighton)

Campus map


Who is this Summer School aimed at?

  • The Summer School is aimed at Mathematics, Astronomy and Physics PhD students at the end of their 1st or 2nd year of study.
  • Places for STFC students are fully-funded, so there is no extra cost. This includes the cost of accommodation and all meals.
  • Accommodation on Sussex University campus will be provided for all registered attendees.
  • If you are not an STFC funded student you are welcome and encouraged to attend: the cost will be £585 including accommodation, meals and all activities.

Registration for the Summer School is now closed.