Eventbrite Link: https://www.eventbrite.co.uk/e/ai3sd-machine-learning-for-chemistry-training-workshop-hackathon-tickets-65426429211

Dataset and Challenges Link: https://docs.google.com/document/d/1Luz0t9QCWHyF9qdycbWvk6ULd9RD_7t8/edit

This training workshop and hackathon is intended to help upskill scientists in AI and Machine Learning techniques for Chemistry and provide some challenges to test out their new skills. This event will run over two days with lunch and dinner provided on day 1 and lunch provided on day 2. Day 1 will begin with some training courses to add to or refresh your knowledge, followed by creating your teams and choosing which challenge you wish to address! There will be mentors on hand to provide advice during the hacking, and there will be pizza provided and the use of the wide lane facilities until 8pm. On day 2, the morning will be spent hacking and after lunch the groups will come together to present their work!

Training Sessions & Talks

• Data Science Awareness Session – Steve Brewer. This training session will provide a general overview of what a data scientist is, from the perspective of working on the EDISON Project.
• Progressing from basic to advanced Machine Learning – Professor Mahesan Niranjan. This training session will introduce some more advanced machine learning methods and demonstrate how to implement them on top of or instead of your basic ML techniques.
• Dataset Training – The different datasets will be introduced including details on what they contain and the apis required to access them.

Challenges & Datasets

1. Solubility Challenge – Dr Nicola Knight

• https://pubs.acs.org/doi/10.1021/acs.jcim.9b00345
• https://www.pub.iapchem.org/ojs/index.php/admet/article/view/686

2. Physical Science Data Science Service and ChEMBL Mashup Challenges – Professor Simon Coles & Dr Tim Rozday

• https://www.psds.ac.uk
• https://www.ebi.ac.uk/chembl/

3. Chemical Safety Challenge – Dr Nick Lynch

• https://www.pistoiaalliance.org/projects/chemical-safety-library/

4. Or Bring your own Challenge! If you have an idea for the next funding application and want to try it out in a hackathon style environment then feel free to bring your own challenge.

Additional Potential useful Datasets

• ChemSpider: http://www.chemspider.com
• PubChem: https://pubchem.ncbi.nlm.nih.gov
• Quantum/DTF Dataset: https://www.nature.com/articles/sdata201422
• Quantum/DTF Dataset: http://quantum-machine.org/datasets/
• Benchmarks: https://pubs.rsc.org/en/content/articlehtml/2018/sc/c7sc02664a

Additional Resources

• Fair Sharing: https://fairsharing.org/
• BioPortal: https://bioportal.bioontology.org/ontologies

Programme

Day 1

• 09:30-10:00: Coffee & Registration
• 10:00-10:15: Welcome Introduction – Professor Jeremy Frey
• 10:15-11:00: Data Science Awareness Session – Steve Brewer
• 11:00-11:45: Progressing from Basic to Advanced Machine Learning – Professor Mahesan Niranjan
• 11:45-12:30: Access to Datasets + Introduction of Challenges
• 12:30-13:30: Lunch & Team Formation
• 13:30-15:00: Hacking
• 15:00-15:15: Coffee Break
• 15:15-16:30: Hacking
• 16:30-17:00: Coffee Break
• 17:00-20:00: Hacking (Pizza and refreshments will be provided at 18:30)

Day 2

• 09:00-09:30: Coffee
• 09:30-11:00: Hacking
• 11:00-11:15: Coffee
• 11:15-12:30: Hacking
• 12:30-13:30: Lunch
• 13:30-14:15: Hacking
• 14:15-15:15: Finalise Work & Prepare Presentations
• 15:15-15:30: Coffee
• 15:30-16:30: Presentations & Feedback
• 16:30-17:00: Wrap Up / Summary Feedback & Prizes

Travelling to the Event

• By Bus: The U1A Bus will take you directly to Southampton Airport Parkway which is just across the road from the Wide Lane Sports Grounds
• By Train: Southampton Airport Parkway is just across the road from the Wide Lane Sports Ground, or if your train can only arrive at Southampton Central or St Denys then you can get the U1A bus from either of these stations to Airport Parkway
• By Car: The postcode for the Wide Lane Sports Ground is SO50 5PE and there will be parking available for delegates. Upon arrival please inform the staff manning the barriers that you are part of this event and they will let you through.
• By Plane: Southampton Airport is just across the road from the Wide Lane Sports Ground.
  Accommodation

Accomodation
If you do not live locally and need somewhere to stay we recommend the Premier Inn by Southampton Airport.

FAQs

1. Who should attend? Anyone with an interest in any of the training, challenges or interested in tackling their own challenge in a hackathon style environment. We welcome members of academia or industry working in or with an interest in any of the science, mathematics or machine learning techniques required for these challenges. Feel free to come as a team, or come by yourself and we will find you a team to work with.
2. What will I get out of it? You will gain useful skills from the training sources, hear about a range of interesting useful data sources and challenges, and have the opportunity to take part in a hackathon in a supportive team environment with mentors and helpers. You will have the opportunity to work with other likeminded people from different academic and industrial backgrounds. There will be lunch and dinner provided on day 1, and lunch on day 2, with multiple coffee breaks throughout the day.
3. What are the aims of the training session / hackathon? The aims of this session are to skill you up on data science and machine learning techniques and given you the opportunity to try these new skills out during the hackathon.