We are pleased to announce that this summer AI4SD will be running a hybrid residential summer school from the 20th-24th June 2022 at the University of Southampton. This summer school will introduce you to basic python programming, different areas of machine learning including mathematical foundations for ML, classification and clustering, kernel methods, introduction to deep learning and case studies in chemistry including reinforcement learning in chemistry. There will also be talks to upskill scientists in other relevant areas including Group Management, Presentation Skills, Research Data Management, Referencing, LaTeX, GitHub and Ethics. The summer school will include a hackathon where students can compete in teams to solve the same problem in the best way. Group presentations will take place on the friday and prizes will be given to the winning team.
The key dates are as follows:
- 10th May 2022 – Applications open
- 6th June 2022 – Deadline for applications (Submitted via our Summer School Application Form)
- 10th June 2022 – Successful applicants announced
- 1st July 2022 – Reports Due in
How to apply
Please fill in the Summer School Application Form and and also get your supervisor or line manager to email s.kanza@soton.ac.uk in support of this application.
Eligibility
To be eligible for this summer school you should be a PhD Student or Early Career Researcher at an eligible UK institution. Higher education institutions, and some research council institutes and independent research organisations are eligible to apply. A list of eligible organisations to apply to EPSRC is provided at: https://www.ukri.org/funding/how-to-apply/eligibility/.
Cost
This summer school is FREE to attend! But we do have a limited number of place (both physically and virtually).
Hackathon Expectations
Groups will present their work from the hackathon challenge on the final day (friday) and will be expected to hand in a short report by the 1st July. There will be a £200 prize for the best group report. Reports MUST be submitted by 00:00 BST on the 1st July to be considered for the prize.
Physical Attendees & Expectations
Accommodation and all meals will be provided as part of the summer school. Due to the high demand for places, attendees will be split across two hotels. The hotels are between 30-50 minutes walk from campus, anyone requiring alternative arrangements can get in touch with us after being accepted. If you live locally and wish to only attend during the day without staying at our provided accommodation that is fine, and in which case lunch will be provided on each day. We do expect you attend each session where possible.
Virtual Attendees
All sessions will take place via zoom and will be recorded and made available. However, as there are only a certain number of places we do expect you to attend each session where possible.
Agenda
Day 1: 20th June | |||
Time | Session | Speaker | Location |
10:00-10:15 | Coffee | 02 Foyer | |
10:15-10:30 | Welcome & Logistics | Dr Samantha Kanza | 02/1083 |
10:30-11:30 | Introduction to Python | Mr Samuel Munday | 02/1083 |
11:30-11:45 | Coffee Break | 02 Foyer | |
11:45-12:15 | Introduction to GitHub | Mr Samuel Munday | 02/1083 |
12:15-13:15 | Lunch Break | 02 Foyer | |
13:15-14:15 | Using RDKit | Mr Samuel Munday | 02/1083 |
14:15-15:15 | ML1: Mathematical Foundations for ML | Prof Mahesan Niranjan | 02/1083 |
15:15-15:30 | Coffee Break | 02 Foyer | |
15:30-16:30 | ML2: Classification and Clustering | Prof Mahesan Niranjan | 02/1083 |
17:00-19:00 | Group BBQ |
Day 2: 21st June | |||
Time | Session | Speaker | Location |
10:00-10:15 | Coffee | 02 Foyer | |
10:15-11:15 | ML3: Kernel methods | Prof Mahesan Niranjan | 02/1083 |
11:15-11:30 | Coffee Break | 02 Foyer | |
11:30-12:30 | ML4: Introduction to Deep Learning | Prof Mahesan Niranjan | 02/1083 |
12:30-13:30 | Lunch Break | 02 Foyer | |
13:30-14:30 | ML5: Case studies in Chemistry | Prof Mahesan Niranjan | 02/1083 |
14:30-15:00 | Project Management & Collaborative Data Management | Dr Samantha Kanza | 02/1083 |
15:00-15:15 | Coffee Break | 02 Foyer | |
15:15-16:30 | Group Formation & Hackathon Introduction | Dr Jo Grundy | 02/1083 |
Day 3: 22nd June | |||
Time | Session | Speaker | Location |
10:00-10:15 | Coffee | 02 Foyer | |
10:15-10:35 | Intro to LaTeX | Dr Samantha Kanza | 02/1083 |
10:35-10:55 | LaTeX & Overleaf | Dr Nicola Knight | 02/1083 |
10:55-11:15 | Ethics & Writing Ethics Applications | Dr Samantha Kanza | |
11:15-11:30 | Coffee Break | 02 Foyer | |
11:30-11:50 | Referencing & Referencing Managers | Dr Nicola Knight | 02/1083 |
11:50-12:10 | Collaborative Presentations & Reports | Dr Samantha Kanza | 02/1083 |
12:10-12:30 | Presentation Skills | Dr Nicola Knight | 02/1083 |
12:30-13:30 | Lunch Break | 02/1083 | |
13:30-15:15 | Group Hackathon Session | 28/1019 | |
15:15-15:45 | Coffee Break | 02 Foyer | |
15:45-16:30 | ML6: Reinforcement Learning in Chemistry | Dr Stephen Gow | 02/1083 |
Day 4: 23rd June | ||
Time | Session | Location |
10:00-10:15 | Coffee | 28 Foyer |
10:15-11:15 | Group Hackathon Session | 28/1019 |
11:15-11:30 | Coffee Break | 28 Foyer |
11:30-12:30 | Group Hackathon Session | 28/1019 |
12:30-13:30 | Lunch Break | 28 Foyer |
13:30-15:00 | Group Hackathon Session | 28/1019 |
15:00-15:15 | Coffee Break | 28 Foyer |
15:15-16:30 | Group Hackathon Session | 28/1019 |
Day 5: 24th June | |||
Time | Session | Speaker | Location |
09:15-09:30 | Coffee | 02 Foyer | |
09:30-10:15 | Group Hackathon Time & Presentation Preparation | 02/1083 | |
10:15-10:45 | Group Presentations | 02/1083 | |
10:45-11:00 | Coffee Break | 02 Foyer | |
11:00-12:15 | Group Presentations | 02/1083 | |
12:15-12:30 | Presentation Feedback | Prof Jeremy Frey & Prof Mahesan Niranjan | 02 Foyer |
12:30-13:30 | Lunch | 02/1083 |