Anagenex | biotech, machine learning | Hybrid (Boston Area - MA) | Junior-MidLevel Data Scientist | Full Time | https://anagenex.com/
We are a series A stage biotechnology company building a novel platform for drug discovery focusing on difficult targets. Machine learning has struggled in early stage drug discovery efforts because most of these efforts do not have enough data for the models to parse. Our technology solves the data problem with massively parallel biochemistry in the form of DNA Encoded Libraries (DELs), allowing us to analyze 100-1000x more compounds compared to traditional approaches. By feeding our algorithms with this data we can identify better compounds faster than competing solutions. We recently closed a substantial Series A, having assembled a highly interdisciplinary team of both bench and computational scientists and proven the technology by showing how our data and ML models improve on the state of the art by 3x-16x depending on the application. Come help us build the future of drug discovery!
Tech Stack: K8S, Python, Spark, AWS, Pytorch
*You’ll own:*
- Bespoke analysis of early stage drug discovery data
- Create Python tools to assist bench scientists in the day-to-day activities
- Work with ML specialists to deliver useful data
*You’ll assist:*
- Maintain and upgrade existing registration and analysis tools
- Processing and validation of large data sets
- Interpreting analyses, including ML results, for bench scientists as needed
*Skills & expertise you have:*
- A BS or MS degree in a Computer Science discipline with 0 – 3 years experience,
- OR a BS/MS Chemistry or Biology degree with at least 3 years professional Python programming experience
- Python programming
- Familiarity with SQL
- Chemistry or Biology lab-based classwork or equivalent experience
- Good communication skills. Mentoring or tutoring experience a plus as this role requires the ability to explain compute-oriented concepts to non-compute professionals
Email me directly if you're interested! henri at anagenex dot com
Anagenex | biotech, machine learning | REMOTE (US) | Senior/Staff/Principal Backend Engineer (Dev/Data/ML Ops) | Full Time | https://anagenex.com/
We are a seed stage biotechnology company building a novel platform for drug discovery focusing on difficult targets. Machine learning has struggled in early stage drug discovery efforts because most of these efforts do not have enough data for the models to parse. Our technology solves the data problem with massively parallel biochemistry in the form of DNA Encoded Libraries (DELs), allowing us to analyze 100-1000x more compounds compared to traditional approaches. By feeding our algorithms with this data we can identify better compounds faster than competing solutions. We recently closed a substantial Series A, having assembled a highly interdisciplinary team of both bench and computational scientists and proven the technology by showing how our data and ML models improve on the state of the art by 3x-16x depending on the application. Come help us build the future of drug discovery!
I do machine learning/data science consulting, mostly for startups. Literally 80% of my time is cleaning data and coding up basic ML for their excel spreadsheets :)
Most of the data outside software startups is in Excel spreadsheets :)
And yes - believe it or not I rolled out a Beta version of an AutoML app for spreadsheets app today!
Email me (email in profile) - not open source but completely free Beta. Just trying to figure out if it's something people would be interested in. (Edit: email rather than DM)
Self plug: If you enjoy this and want some (less technical) insight on connections between ML and thermodynamics, you might enjoy my series of blog posts: http://henripal.github.io/blog/stochasticdynamics
Cool.
I'm guessing from trying it out that you're using Highcharts.
I've run into really unpleasant memory leaks/slowness when streaming data (especially when the existing chart is already thousands of data points). Are you seeing something similar?
Yes using Highcharts. You've had issues with Highcharts? Yeah it's not designed to stream data extremely rapidly but it's a great "good enough" product, especially for something like Losswise where the differentiation is the overall design and architecture and developer experience, not the prettiest possible graphs.
Yes... For example if I'm running three experiments at the same time, auto-refreshing the chart every two seconds, it essentially freezes the app to a crawl after a thousand points or so. So we reverted to manual updates.
As a Highcharts developer, I had a look at your benchmarking, and have some thoughts about optimizing for Highcharts. The first step is to turn off animation, which helps a lot. The default Highcharts animation on addPoint is 250ms, so with a refresh rate of 100ms you will get a lot of redrawing going on for nothing. The second thing that possibly optimizes a bit is to use hard-coded axis values so that it doesn't have to recompute axis values for each iteration.
Yeah I have no idea. If you need really high performance that Highcharts doesn't provide you probably need to write your own specialized charting library.
For those of you who want to tinker, there's a much rougher, open source library based on Vuejs, postgres, and Flask with some momentum on GitHub right now, LabNotebook https://github.com/henripal/labnotebook
We are a series A stage biotechnology company building a novel platform for drug discovery focusing on difficult targets. Machine learning has struggled in early stage drug discovery efforts because most of these efforts do not have enough data for the models to parse. Our technology solves the data problem with massively parallel biochemistry in the form of DNA Encoded Libraries (DELs), allowing us to analyze 100-1000x more compounds compared to traditional approaches. By feeding our algorithms with this data we can identify better compounds faster than competing solutions. We recently closed a substantial Series A, having assembled a highly interdisciplinary team of both bench and computational scientists and proven the technology by showing how our data and ML models improve on the state of the art by 3x-16x depending on the application. Come help us build the future of drug discovery!
Tech Stack: K8S, Python, Spark, AWS, Pytorch
*You’ll own:*
- Bespoke analysis of early stage drug discovery data - Create Python tools to assist bench scientists in the day-to-day activities - Work with ML specialists to deliver useful data
*You’ll assist:*
- Maintain and upgrade existing registration and analysis tools - Processing and validation of large data sets - Interpreting analyses, including ML results, for bench scientists as needed
*Skills & expertise you have:*
- A BS or MS degree in a Computer Science discipline with 0 – 3 years experience, - OR a BS/MS Chemistry or Biology degree with at least 3 years professional Python programming experience - Python programming - Familiarity with SQL - Chemistry or Biology lab-based classwork or equivalent experience - Good communication skills. Mentoring or tutoring experience a plus as this role requires the ability to explain compute-oriented concepts to non-compute professionals
Email me directly if you're interested! henri at anagenex dot com