ntenenz

Microsoft Research is hiring Senior MLE's in Cambridge, MA (ONSITE).

Responsibilities include the training of generative models and anything that contributes to the betterment of their capabilities -- profiling / optimizing their throughput, scaling training runs, tuning of hyperparameters / data mixes, etc. If it makes the model better, it's fair game!

Depending on the project, you will likely be involved in some combination of AR model training, diffusion model training, midtraining, post-training, multimodal training, etc.

As you can likely surmise, we're looking for folks who are flexible and comfortable wearing many hats. If this sounds like you and you're interested in working in a research environment, consider applying!

https://apply.careers.microsoft.com/careers/job/197039355664...

This is horrendously incorrect. Surgical masks do not filter aerosolized particles at the same effiency as an N95. For an airborn virus, that's a pretty big deal, especially for HCP who are constantly exposed to high viral loads.

The EULA is attached up the drivers. Newer versions of CUDA often require newer drivers, so you bump into the issue regardless of when you buy the GPU.

`required` was removed due to the challenges it introduces in designing backwards-compatible API changes[1].

[1] https://github.com/protocolbuffers/protobuf/issues/2497#issu...

For those who don't recognize the author's name, https://en.wikipedia.org/wiki/HAProxy

Most MRI's are nowhere near 10T. Scanners in hospitals are typically either 1.5T or 3T. 7T exists, but is _extremely_ rare in clinical practice.

MGH & BWH Center for Clinical Data Science | Boston, MA USA | ONSITE, Full-Time, VISA | https://www.ccds.io

At the CCDS, we're applying machine learning to healthcare to improve patient care and reduce inefficiency. Unlike most healthcare startups, we are embedded within a hospital (two actually -- Mass General Hospital and Brigham & Women's Hospital) giving us access to the clinicians and data we need to solve the most important issues facing medicine today. And with support from Nvidia, GE, and Nuance, we have the hardware, translational expertise, and financial support to execute on our mission.

We're expanding aggressively and are hiring across the org. In particular, the ML team will be scaling and is seeking skilled engineers with varying levels of ML experience, from junior roles for those with less time in industry to more senior positions for those who have a proven track record of shipping product. We offer competitive salaries, visa sponsorship, (unsurprisingly) great health benefits, and a mission that you can be proud to describe to friends and family.

If interested, feel free to reach out (contact info in profile). I'm Director of ML for the org and will personally respond to any questions you may have.

MGH & BWH Center for Clinical Data Science | Boston, MA USA | ONSITE, Full-Time, VISA | https://www.ccds.io At the CCDS, we're applying machine learning to healthcare to improve patient care and reduce inefficiency. Unlike most healthcare startups, we are embedded within a hospital (two actually -- Mass General Hospital and Brigham & Women's Hospital) giving us access to the clinicians and data we need to solve the most important issues facing medicine today. And with support from Nvidia, GE, and Nuance, we have the hardware, translational expertise, and financial support to execute on our mission.

We're expanding aggressively and are hiring across the org. In particular, the ML team will be scaling and is seeking skilled engineers with varying levels of ML experience, from junior roles for those with less time in industry to more senior positions for those who have a proven track record of shipping product. We offer competitive salaries, visa sponsorship, (unsurprisingly) great health benefits, and a mission that you can be proud to describe to friends and family.

If interested, feel free to reach out (contact info in profile). I'm Director of ML for the org and will personally respond to any questions you may have.

MGH & BWH Center for Clinical Data Science | Boston, MA USA | ONSITE, Full-Time, VISA

At the CCDS, we're applying machine learning to healthcare to improve patient care and reduce inefficiency. Unlike most healthcare startups, we are embedded within a hospital (two actually -- Mass General Hospital and Brigham & Women's Hospital) giving us access to the clinicians and data we need to solve the most important issues facing medicine today. And with support from Nvidia, GE, and Nuance, we have the HW, translational expertise, and financial support to execute on our mission.

We're hiring for multiple roles on our ML, SW, Product, Data Eng, and Infrastructure teams. If interested, feel free to reach out (contact info in profile).

For more info, visit https://www.ccds.io/job-openings

Please do. Unfortunately I've been swamped the last few weeks with prep for the world's largest radiology conference, so I'm a bit behind schedule.

MGH & BWH Center for Clinical Data Science | Boston, MA USA | ONSITE, Full-Time, VISA | https://www.ccds.io

At the CCDS, we're applying machine learning to healthcare to improve patient care and reduce inefficiency. Unlike most healthcare startups, we are embedded within a hospital (two actually -- Mass General Hospital and Brigham & Women's Hospital) giving us access to the clinicians and data we need to solve the most important issues facing medicine today. And with support from Nvidia, GE, and Nuance, we have the hardware, translational expertise, and financial support to execute on our mission.

We're expanding aggressively and are hiring across the org. In particular, the ML team will be scaling and is seeking skilled engineers with varying levels of ML experience, from junior roles for those with less time in industry to more senior positions for those who have a proven track record of shipping product. We offer competitive salaries, visa sponsorship, (unsurprisingly) great health benefits, and a mission that you can be proud to describe to friends and family.

If interested, feel free to reach out (contact info in profile). I'm Director of ML for the org and will personally respond to any questions you may have.

MGH & BWH Center for Clinical Data Science | Boston, MA USA | ONSITE, Full-Time, VISA | https://www.ccds.io

At the CCDS, we're applying machine learning to healthcare to improve patient care and reduce inefficiency. Unlike most healthcare startups, we are embedded within a hospital (two actually -- Mass General Hospital and Brigham & Women's Hospital) giving us access to the clinicians and data we need to solve the most important issues facing medicine today. And with support from Nvidia, GE, and Nuance, we have the hardware, translational expertise, and financial support to execute on our mission.

We're expanding aggressively and are hiring across the org. In particular, the ML team will be scaling and is seeking skilled engineers with varying levels of ML experience, from junior roles for those with less time in industry to more senior positions for those who have a proven track record of shipping product. We offer competitive salaries, visa sponsorship, (unsurprisingly) great health benefits, and a mission that you can be proud to describe to friends and family.

If interested, feel free to reach out (contact info in profile). I'm Director of ML for the org and will personally respond to any questions you may have.

MGH & BWH Center for Clinical Data Science | Boston, MA USA | ONSITE, Full-Time, VISA | https://www.ccds.io

At the CCDS, we're applying machine learning to healthcare to improve patient care and reduce inefficiency. Unlike most healthcare startups, we are embedded within a hospital (two actually -- Mass General Hospital and Brigham & Women's Hospital) giving us access to the clinicians and data we need to solve the most important issues facing medicine today. And with support from Nvidia, GE, and Nuance, we have the hardware, translational expertise, and financial support to execute on our mission.

We're expanding aggressively and are hiring across the org. In particular, the ML team will be scaling and is seeking skilled engineers with varying levels of ML experience, from junior roles for those with less time in industry to more senior positions for those who have a proven track record of shipping product. We offer competitive salaries, visa sponsorship, (unsurprisingly) great health benefits, and a mission that you can be proud to describe to friends and family.

If interested, feel free to reach out (contact info in profile). I'm Director of ML for the org and will personally respond to any questions you may have.

Hi Rishi,

Feel free to reach out via email (see my profile) where I can answer any questions you may have.

- Neil

MGH & BWH Center for Clinical Data Science | Boston, MA USA | ONSITE, Full-Time, VISA | https://www.ccds.io

At the CCDS, we're applying machine learning to healthcare to improve patient care and reduce inefficiency. Unlike most healthcare startups, we are embedded within a hospital (two actually -- Mass General Hospital and Brigham & Women's Hospital) giving us access to the clinicians and data we need to solve the most important issues facing medicine today. And with support from Nvidia, GE, and Nuance, we have the hardware, translational expertise, and financial support to execute on our mission.

We're expanding aggressively and are hiring across the org. In particular, the ML team will be scaling and is seeking skilled engineers with varying levels of ML experience, from junior roles for those with less time in industry to more senior positions for those who have a proven track record of shipping product. We offer competitive salaries, visa sponsorship, (unsurprisingly) great health benefits, and a mission that you can be proud to describe to friends and family.

If interested, feel free to reach out (contact info in profile). I'm Director of ML for the org and will personally respond to any questions you may have.

A pretty glaring example is this one (LDAP password stored in plaintext): https://gitlab.com/gitlab-org/gitlab-ce/issues/38066

We purchased a gitlab subscription but cannot obtain infosec approval (and thus cannot use it) due to this issue.

While most can learn to ride a bicycle with minimal effort, it turns out the control of an idealized bicycle is actually quite complex and has a storied history. For a brief rundown (and insight into the complexity of the problem), scan through this presentation (pdf warning): http://www.control.lth.se/media/Staff/KarlJohanAstrom/Lectur...

MGH & BWH Center for Clinical Data Science | Boston, MA USA | ONSITE, Full-Time, VISA

At the CCDS, we're applying machine learning to healthcare to improve patient care and reduce inefficiency. Unlike most healthcare startups, we are embedded within a hospital (two actually -- Mass General Hospital and Brigham & Women's Hospital) giving us access to the clinicians and data we need to solve the most important issues facing medicine today. And with support from Nvidia, GE, and Nuance, we have the HW, translational expertise, and financial support to execute on our mission.

We're hiring for multiple roles on our ML, SW, Product, Data Eng, and Infrastructure teams. If interested, feel free to reach out (contact info in profile).

For more info, visit https://www.ccds.io/job-openings

Unfortunately, these are of the older gen w/16GB of RAM rather than 32GB which is now available. https://www.nvidia.com/en-us/data-center/tesla-v100/

For those interested, the DAWN Trial (http://www.nejm.org/doi/full/10.1056/NEJMoa1706442) provides more detail on the value of thrombectomy, especially in cases where the collateral circulation is strong.

When Hinton approves, you know you've done well...

https://www.reddit.com/r/MachineLearning/comments/7ew7ba/d_c...

MGH & BWH Center for Clinical Data Science | Boston, MA USA | ONSITE only

At the CCDS, we're applying machine learning to healthcare to improve patient care and reduce inefficiency. Unlike most healthcare startups, we are embedded within a hospital (two actually -- Mass General Hospital and Brigham & Women's Hospital) giving us access to the clinicians and data we need to solve the most important issues facing medicine today. And with support from Nvidia and GE, we have the HW, translational expertise, and financial support to follow through on our mission.

We're hiring for multiple roles, including Lead Software Engineer, Software Engineer, PM, and HPC Lead . If interested, feel free to reach out (contact info in profile).

For more info, https://clindatsci.com/jobs

MGH & BWH Center for Clinical Data Science | Boston, MA USA | ONSITE only

At the CCDS, we're applying machine learning to healthcare to improve patient care and reduce inefficiency. Unlike most healthcare startups, we are embedded within a hospital (two actually -- Mass General Hospital and Brigham & Women's Hospital) giving us access to the clinicians and data we need to solve the most important issues facing medicine today. And with support from Nvidia and GE, we have the HW, translational expertise, and financial support to follow through on our mission.

We're hiring for multiple roles, including Data Engineer, PM, Software Dev, and Lead Software Dev. If interested, feel free to reach out (contact info in profile).

For more info, https://clindatsci.com/jobs

One of the reasons people have shifted away from MNIST is that it's simply too easy. Single channel, small image size, few classes, etc. Unfortunately, this does not address any of these concerns.

Holy data leakage Batman!

Because the data augmentation is performed prior to the random train/val/test split, nearly identical instances may be found in each set. In other words, a 1 degree rotation of training image X may be found in the validation or test set which would artificially inflate performance.

I mean this in the nicest possible way (so please don't take offense), but I think you're missing what is being said there. The framework itself should have no impact, positive or negative, on model accuracy. That being said, it can be extremely challenging to reproduce results given the stochasticity of random batches and asynchronous updates. Furthermore, precisely specifying the methods of data augmentation can be tedious, thus the protocol is often only partially detailed in published work which further exacerbates the challenges of reproducing results.

Assessing accuracy? If you're running the same architecture with the same training regime, why would you expect differing accuracy numbers (other than a bug of some sort)? Seems a bit strange to include.