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sgbaird committed Feb 21, 2024
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---
layout: page
title: BO Hackathon for Chemistry and Materials
title: Bayesian Optimization Hackathon for Chemistry and Materials
menu_title: Home
menu_icon: house-door
---
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{% endif %}

{:.secondary}
# {{ site.event_date }}, in association with the Acceleration Consortium and Merck KGaA
# {{ site.event_date }}, sponsored by the Acceleration Consortium and Merck KGaA

<div class="aside">
<h2><i class="bi bi-calendar3"></i> Event timeline</h2>
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Researchers can sign up to [topics such as]({{ site.baseurl }}{% link projects.md %})
applying algorithms to existing benchmarks, developing new benchmark tasks, creating instructional tutorials, and proposing real-world chemistry and materials optimization tasks. [This opportunity]({{ site.baseurl }}{% link registration.md %})
is open to researchers at all levels who are interested in applying Bayesian optimization[<sup>(?)</sup>][faq]{:title="Are algorithms other than Bayesian optimization allowed?"} for accelerated discovery in chemistry and materials science. At minimum, to participate in code-focused projects, we recommend beginner-to-intermediate Python programming experience and basic familiarity with git and GitHub.[<sup>(?)</sup>][faq]{:title="Am I eligible to participate in the hackathon?"}. Training resources are available on the [resources page](_/../resources.md).
is open to researchers at all levels who are interested in applying Bayesian optimization[<sup>(?)</sup>][faq]{:title="Are algorithms other than Bayesian optimization allowed?"} for accelerated discovery in chemistry and materials science. For code-focused projects, we recommend beginner-to-intermediate Python programming experience and basic familiarity with git and GitHub.[<sup>(?)</sup>][faq]{:title="Am I eligible to participate in the hackathon?"}. Training resources are available on the [resources page](_/../resources.md).

## Logistics

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