This position is open to remote work within the US or onsite work at our headquarters in South San Francisco. Our working hours are 9-5pm PT. Freenome is a high-growth biotech company on a mission since 2014 to create tools that empower everyone to prevent, detect, and treat their disease. To achieve this mission, Freenome is developing next-generation blood tests to detect cancer in its earliest, most treatable stages using our multiomics platform and machine learning techniques. Our first blood test will detect early-stage colorectal cancer and advanced adenomas.

Freenome is known for seeing what humans cannot see. By decoding cell-free biomarker patterns of once-unthinkable complexity, Freenome's blood tests are powered by its multi-omics platform and designed to detect cancer with the help of machine learning and molecular biology at its earliest stages to help clinicians optimize treatments and the next generation of precision therapies. By training on thousands of cancer-positive blood samples, Freenome's multi-omics platform learns which biomarker patterns signify cancer's type and effective treatment pathways. Training on healthy samples helps experts to establish what a normal composition of cell-free biomarkers should look like. This unique concept of Freenome makes the company stand out among all.

Freenome is known for seeing what humans cannot see. By decoding cell-free biomarker patterns of once-unthinkable complexity, Freenome's blood tests are powered by its multi-omics platform and designed to detect cancer with the help of machine learning and molecular biology at its earliest stages to help clinicians optimize treatments and the next generation of precision therapies. By training on thousands of cancer-positive blood samples, Freenome's multi-omics platform learns which biomarker patterns signify cancer's type and effective treatment pathways. Training on healthy samples helps experts to establish what a normal composition of cell-free biomarkers should look like. This unique concept of Freenome makes the company stand out among all.

Entopsis: Entopsis is a Miami based startup building a device NuTec (Nanoscale Unbiased Textured Capture) utilizing artificial intelligence. NuTec is mainly focussed on cancer, autoimmune diseases. SkinVision: SkinVision is a skin cancer awareness and tracking app that allows you to understand your risk factors for skin cancer and keep track of your moles. CureMetrix: CureMetrix is developing a next-generation based medical image analysis tool for mammography. OncoraMedical: Oncora Medical is focussed on using machine learning and big data in radiation oncology. This clinical decision support software will provide aid to oncologists based on the results of sophisticated data analytics.

It would be hard to argue that that there is a dearth of artificial intelligence platforms trying to get into the healthcare game. But it isn't just developers deciding where the industry is heading; it's also up to the healthcare players holding the purse strings. "Investors get a different view into technology than a lot of folks, and the decisions they make about where to put capital have big implications for what kind of technology, medicines, and products get developed," Meg Tirrell, a reporter at CNBC and a moderator for this week's AI World Medical Innovation Forum in Boston, said during an investor-focused panel discussion. At the conference, where key investors in the field came together to talk about where they see the future of AI, most agreed that, in general, implementation of AI is in its very early stages and somewhat burdened by hype. "I just went to HIMSS' conference and there were about 5,000 vendors, and almost all of them said they do AI, machine learning, patient engagement, and blockchain. But when you talk to them, few of them are using AI; most of them are algorithmic," Dr. Joe Cunningham, managing director at Sante Ventures, said during the session.

Artificial intelligence hit some key milestones in 2017. At Facebook, chat bots were able to negotiate as well as their human counterparts. A poker-playing system designed by Carnegie Mellon professors mopped the floor with live opponents. There were even some potentially life-saving breakthroughs, like the machine vision system that can determine whether a mole is cancerous with more than 90 percent accuracy--beating out a group of dermatologists. From agriculture to medicine and beyond, plenty of startups are using A.I. in innovative ways.

AI, applied properly in healthcare, will save lives, said Freenome's CEO Gabriel Otte. Freenome, an AI 100 startup working on cancer diagnostics, is backed by Andreessen Horowitz, Data Collective, and Founders Fund. The healthcare AI category has been heating up, with around 50 new companies raising their first equity after January 2015. During the panel discussion on AI's Transformation of Healthcare at the Innovation Summit, Otte stressed the importance of taking healthcare AI "step by step" to minimize risk to patients' lives. "I think we should also keep in mind that all diagnostics is subjective today. It's up to the doctor [to make the final decision]… The concept of having an AI make that decision is still many, many years away," Otte said, dismissing the dystopian notion of "machines killing people."

If Gabe Otte '11 hadn't had a Cornell advisor who steered him down a more challenging path and hadn't had some chance conversations with Nobel Prize-winning chemist Roald Hoffman, he might be squirreled away in a lab somewhere. Instead, he's the CEO of Freenome, a start-up just awarded 5.5 million in venture capital for its product, a data-driven blood test that can detect various types of cancers in their earliest stages and recommend the best treatments. Otte came to Cornell planning to study computer science, but a freshman-year advisor encouraged him to choose another major. "I had been coding and programming since I was nine years old," Otte said, so he elected to study chemistry and computational biology, using his knack for computer science to do his homework. "I fell in love with chemistry when I took organic chemistry," he said, adding that he developed his own computer program to do computations related to the synthesis of molecules.