We are continuously looking for reliable and knowledgable people to join our team:
A) As a Machine Learning Scientist Intern you have (ideal if you are currently in a PhD program): - Expertise in Bayesian Optimisation and Gaussian Processes - Experience in an industry setting and how to work with client engineers - Concise and honest communication
B) As a Django Engineer, you have: - A portfolio of web projects to showcase your skill - Experience in Django or ability to learn it fast - Concise and honest communication
I put together SDL4Kids as a community project to lower the barrier of entry into this fast growing space of 'self-driving' laboratories.
I love how in the UK, many schools will already have the BBC micro:bit lying around, so many school kids have a real chance at trying themselves at this setup.
Matterhorn Studio | 2 Open Roles: Machine Learning Scientist (Intern), Django Engineer| Remote/London/Oxford | Full-Time | http://matterhorn.studio
At Matterhorn Studio we support materials companies in their first step towards integrating Machine Learning in their R&D process. Try our 5 minute tutorial on http://matterhorn.studio to get an idea of what that looks like in practice. You can learn more about this research field from our blog as well: https://matterhorn.studio/pages/blog/
We are continuously looking for reliable and knowledgable people to join our team.
A) As a Machine Learning Scientist Intern you have (ideal if you are currently in a PhD program): - Expertise in Bayesian Optimisation and Gaussian Processes - Experience in an industry setting and how to work with client engineers - Concise and honest communication
B) As a Django Engineer, you have: - A portfolio of web projects to showcase your skill - Experience in Django or ability to learn it fast - Concise and honest communication
Matterhorn Studio | 2 Open Roles: Machine Learning Scientist (Intern), Django Engineer| Remote/London/Oxford | Full-Time | http://matterhorn.studio
At Matterhorn Studio we support materials companies in their first step towards integrating Machine Learning in their R&D process. Try our 5 minute tutorial on http://matterhorn.studio to get an idea of what that looks like in practice.
You can learn more about this research field from our blog as well: https://matterhorn.studio/pages/blog/
We are continuously looking for reliable and knowledgable people to join our team.
A) As a Machine Learning Scientist Intern you have (ideal if you are currently in a PhD program):
- Expertise in Bayesian Optimisation and Gaussian Processes
- Experience in an industry setting and how to work with client engineers
- Concise and honest communication
B) As a Django Engineer, you have:
- A portfolio of web projects to showcase your skill
- Experience in Django or ability to learn it fast
- Concise and honest communication
Matterhorn Studio | Research Scientist (Intern) | Remote/London/Oxford | Full-Time | http://matterhorn.studio
At Matterhorn Studio we support materials companies in their first step towards integrating Machine Learning in their R&D process. Try our 5 minute tutorial on http://matterhorn.studio to get an idea of what that looks like in practice.
We are continuously looking for reliable and knowledgable people to join our team. Specifically, you have:
- Expertise in Bayesian Optimisation and Gaussian Processes
- Experience in an industry setting and how to work with client engineers
- Concise and honest communication
At the moment we are looking for a Research Scientist Intern, which is ideal if you are currently in a PhD program, but we are also open for general applications of interest.
Not involved with causal.app, but I see it as going the other way as far as causality goes. Pearl-style models are trying to infer causation from data. Here, you give it a causal model that encapsulates how you think a scenario works (which variables affect the outcome, how, and a range of likely values for them), and it simulates your model to give you ranges of likely outcomes, plus some other things like sensitivity analysis (which variables impact likely outcomes the most). I like the comparison they make to spreadsheet models. It's that style of modeling but with Monte Carlo simulations, so you can put ranges instead of single numbers in cells, and the ranges propagate through the model to output ranges.
At Matterhorn Studio we support materials companies in their first step towards integrating Machine Learning in their R&D process.
Try our 5 minute tutorial on http://matterhorn.studio to get an idea of what that looks like in practice.
You can learn more about this research field from our blog as well: https://matterhorn.studio/pages/blog/
We are continuously looking for reliable and knowledgable people to join our team: A) As a Machine Learning Scientist Intern you have (ideal if you are currently in a PhD program): - Expertise in Bayesian Optimisation and Gaussian Processes - Experience in an industry setting and how to work with client engineers - Concise and honest communication B) As a Django Engineer, you have: - A portfolio of web projects to showcase your skill - Experience in Django or ability to learn it fast - Concise and honest communication
Learn more on these two positions here: https://matterhorn.studio/pages/careers/
Please email Jakob on [email protected] to apply.