TechBio’s next generation

Before Noetik: ‍

SVP, Head of Research at Recursion (RXRX), Early employee from Seed through IPO. Stanford University M.D, Ph.D in Neuroscience.

Why Noetik: ‍

"We founded NOETIK from the observation that we're facing a translation gap between basic drug discovery science and therapeutics success in the clinic. That gap is impacting the progress for patients and is unacceptable. Today we're at an inflection point where the convergence of computational methods and biology at scale can transform how we're discovering and developing drugs. We founded NOETIK to build the AI biotech of the future."

Before Noetik: ‍

Head of Oncology at Recursion. Genentech comp bio (deep learning for cancer vaccines, target discovery for breast cancer, transfer learning for IO biomarkers, high-dimensional data visualization, next-gen SERDs), Stanford.

Why Noetik: ‍

"We’re at a juncture in the biological sciences, with new paradigms emerging. We need new institutions and new ways of working to make sure we  bring new medicines to patients. This is how the future gets built."

Before Noetik: ‍

VP of Informatics at Parker Institute for Cancer Immunotherapy; startup experience applying data science to biology across domains; Cancer survivor.

Why Noetik: ‍

“Everything about Noetik’s mission resonated with me. We need to create detailed images of tumor samples to understand the complex interaction of the tumor and immune system. We need to control data generation to truly enable modern machine learning. And we need all of this, plus a great team, to make better drugs for cancer patients.”

Before Noetik: ‍

Chief Corporate Development Officer at Recursion for four years as well as the interim CMO for half that time. CEO of Navire Pharma and CoA Therapeutics (subsidiaries of BridgeBio Pharma) prior to Recursion. 13-year long tenure at Genentech/Roche as VP and Global Head of Neuroscience, Ophthalmology and Rare disease partnering. University of Nottingham, MD.

Why Noetik: ‍

"These are some of the most passionate and smart people I have worked with before and I am certain will move the needle in cancer therapeutics. The platform capabilities they have built in such a short amount of time are truly impressive in terms of furthering precision medicine in oncology using modern tools and technologies - I’m excited for the opportunity to help further Noetik’s mission."

Before Noetik: ‍

Post-doc at the UCSF Diabetes Center, investigating the development of the pancreas in mice and in zebrafish. Platform development at Fluidigm and Deepcell, focusing on multimodal, high-dimensional tissue and single-cell profiling assays including proteomics, transcriptomics, and AI-based morphology analysis.

Why Noetik: ‍

"I am thrilled to leverage my expertise in Spatial Biology and AI to contribute to Noetik's crucial mission: forging a new path towards precision medicine."

Before Noetik: ‍

Vice President, Head of Operations at Terray Therapeutics (DNA-encoded library synthesis and optical decoding); Director of New Process Implementation & High-throughput Screening at Recursion (integrating new technology into the core platform and running day-to-day operations) ); Product & Application Manager at Bruker Nano (both single molecule and spatial biology technologies). University of Utah PhD in Physics, University of California, Berkeley MBA.

Why Noetik: ‍

"I’m thrilled to join Noetik for the simple reason that I feel its mission is the future of cancer research. Noetik’s expertise and scale in spatial profiling is incredible for such a young company and I am excited to help expanding its custom discovery engine through an inclusive, collaborative team effort."

Before Noetik: ‍

Six years of experience as a computer vision and AI researcher. Built self-supervised, multimodal models for domains where labeled data are difficult or impossible to collect as a postdoc at Stanford and was founder and CEO of a stealth SSL startup. Ph.D. in Neuroscience and an A.B. in Molecular and Cellular Biology from Harvard University.

Why Noetik: ‍

"We're at a key moment where AI can help us discover new, therapeutically crucial biology that would otherwise go unseen. NOETIK's emphasis on building an interdisciplinary team and creating massive, multimodal datasets of real human biology -- in all its complexity -- is exactly the way to take advantage of AI's recent progress."

Before Noetik: ‍

Senior Machine Learning Scientist at Herophilus focused on developing deep learning models, data pipelines and visualizations for cellular segmentation, calcium imaging and organoid growth optimization.

Why Noetik: ‍

“I was excited by Noetik's straightforward strategy of leveraging a highly experienced lab team and next generation multiplex imaging instruments to generate massive multimodal datasets that offer novel insights into cancer biology.”

Before Noetik: ‍

Full stack developer with more than 12 years experience shipping production software. Worked in companies from 6 to 6,000 people all across the stack from Rally to Twitter.

Why Noetik: ‍

"I wanted to use all I've learned about engineering software systems to directly improve people's lives. Noetik is on the frontier at the intersection of biology and engineering and has the opportunity to make a massive impact."

Before Noetik: ‍

Principal AI Scientist at a stealth research startup focused on building flexible and queryable self-supervised learning systems. PhD in neuroscience at Stanford University, where he developed neural networks that predict the structure, function, and development of the human visual system.

Why Noetik: ‍

"Working at Noetik provides the rare opportunity to make progress on truly meaningful problems by developing cutting-edge machine learning approaches that are powered by rich, exciting data. Pursuing those goals as part of a talented and highly collaborative team is the most rewarding work I’ve done in my scientific career."

Before Noetik: ‍

Worked in clinical and research labs for 15 years across a variety of experiments.

Why Noetik: ‍

“It’s an honor to work at Noetik and be part of a team of scientists, machine learning researchers, and software engineers. The culture is special, it’s transparent and sincere. It feels good to always be made aware of Noetik’s plans and goals.”

Before Noetik: ‍

Biotech platform optimization, focused on the clinical study of solid tumor processing, at Atreca, Grail, OncoNano Medicine and Genomic Health.

Why Noetik: ‍

“Everyone at Noetik is listened to equally, and is low-ego and collaborative, despite having different backgrounds and experiences. With that kind of culture we can think outside the box and push boundaries.”

Before Noetik: ‍

Machine Learning Engineer on the ML Platform team at Recursion. Helped build scalable ML systems and performed computer vision research on high-content biological imagery datasets.

Why Noetik: ‍

“I believe in the potential of immune therapy to improve patient outcomes and the power of machine learning to improve drug discovery.”

Before Noetik: ‍

PhD from Stanford and spent 11 years at Genentech. Experienced preclinical researcher in neuroscience and biomarker operations in cancer immunotherapy.

Why Noetik: ‍

“I’m excited to be a part of the highly energetic and productive Noetik team. I love being at the intersection of multiple fields and Noetik presents an amazing opportunity to collaborate cross-functionally in the fight against cancer.”

Before Noetik: ‍

Senior Scientific Manager in Genentech’s Cancer Immunology department for the past 9 years - moving programs from preclinical stage to early clinical development. My PhD and post-docs focused on studying the interactions between various viruses and the immune system, as well as developing novel biomarkers for multiple disease areas.

Why Noetik: ‍

"Noetik offers a unique opportunity to study how antitumor immunity is shaped by the spatial and functional organization of tumors, which I believe offers opportunities for novel therapeutic and precision medicine approaches. And the close collaboration between cutting edge computational and experimental scientists makes this exploration thrilling!"

Before Noetik: ‍

PhD in computational physics working with novel 2D semiconductors. As a postdoc, researched the implementation of ML models to describe conductivity and efficiency of solar cells at the chemical engineering department of UC Davis. Led to working with tech-bios in data-driven drug screens searching for cures for neurological diseases.

Why Noetik: ‍

“With my experience, I've seen how ML and data-driven research can solve efficiency problems and make a great impact in the real world. At Noetik, I believe we have the right combination of technology, science, and motivation to unveil the future of cancer treatments.”

Before Noetik: ‍

Postdoctoral research at Icahn School of Medicine focused on immuno-oncology; Associate Director of Early Discovery at ImmunAI.

Why Noetik: ‍

"Noetik has a strong commitment to spatial profiling: to understand – and target – the underlying causes of disease, we need to better understand how cells function and interact within the tissue. Our discovery engine combines multimodal datasets from large clinical cohorts and from a high-throughput perturbation platform in custom-made, clinically relevant in vivo models of disease. Purposefully building in parallel both the clinical and pre-clinical datasets from the start allows for a cross-species data integration, significantly accelerating the discovery process."

Before Noetik: ‍

PhD in computer science at Cornell University, where she studied algorithms & AI and worked on computational models contact tracing.

Why Noetik: ‍

"I wanted to apply my background in machine learning to work on a problem I truly believed in. I’m excited to work on cutting-edge AI, with unprecedented data, on such an energetic team."

Before Noetik: ‍

Ph.D. in Molecular Medicine from the University of Maryland, School of Medicine. Associate Director of Venture at The Johns Hopkins University supporting all stages of startups and entrepreneurial faculty.

Why Noetik: ‍

“The compelling potential and impact Noetik can have on enhancing oncology treatments, coupled with an amazing and highly capable team, left me convinced this was something I wanted to be a part of.”

Before Noetik: ‍

Extensive experience building software and working in the cancer biology field. Bachelor’s degree from Stanford University, where he double majored in Biology and Computer Science, followed by a master’s degree in Computational Biology from UCSF. Years of hands-on experience working with scientists and biological data through extensive wet lab work. Previously worked at Grail, where he optimized and maintained their R infrastructure, and at The Parker Institute for Cancer Immunotherapy, where he developed tools to streamline and automate workflows for biologists, clinical biostatisticians, and data scientists.

Why Noetik: ‍

"I chose to work at Noetik because their mission to leverage AI for cancer immunotherapy aligns with both my professional experience and personal passion. I have seen the impact of cancer in my family, and it has driven me to use my skills to improve the lives of cancer patients. Noetik’s innovative approach offers a real opportunity to make a positive difference in the world, and I believe that my many years of experience building software in the cancer biology space will make a meaningful contribution to that mission."

Before Noetik: ‍

Pathology lab manager with extensive experience and clinical expertise. Time spent with several startups, Gladstone Institutes, and UCSF.

Why Noetik: ‍

“As someone who’s always worked in labs investigating cancer, Noetik’s science is what gets me super excited. We have a clear vision on how to push the science and technology to discover cancer drugs, and it’s innovative, interesting and hands-on.”

Before Noetik: ‍

Two years of medical school before dropping out to pursue a career in tech; Several startups focused on machine learning in general tech.

Why Noetik: ‍

“Being able to vertically integrate lab work with data science is what rekindled my spark for advancing medicine. While I didn’t like the hierarchy of traditional medicine, Noetik is team oriented; we’re pushing toward a common goal. I feel more hopeful now that I can work at the intersection of health and technology.”

Before Noetik: ‍

Post Doc at Genentech, elucidating the mechanisms of resistance to cancer therapy through the analysis of clinical trial biomarker data. Explored the development of predictive biomaker based on multi-modal data to enhance the selection of patient populations for checkpoint blockade and receptor kinase inhibitor therapies. Ph.D. in Cancer Biology and Genomics from the University of Southern California.

Why Noetik: ‍

"I am enthusiastic about the utilization of Artificial Intelligence and Machine Learning in the realm of drug development at scale. I firmly believe that Noetik's spatially resolved multi-modal platform has the potential to revolutionize precision oncology. Through the integration of high-quality human spatial data and state-of-the-art AI/ML models, we have the capability to gain profound insights into the optimization of patient targeting. Taking into account both the characteristics of the tumor and its microenvironment. "

Before Noetik: ‍

PhD in August 2023 from a joint program between Memorial Sloan Kettering Cancer Center and Cornell University under the guidance of Dr. Dana Pe’er. Focused on harnessing computer vision and ML techniques to study tumor progression and metastasis using high-dimensional single-cell sequencing and spatially-resolved multiplexed imaging.

Why Noetik: ‍

“The vast tapestry of biology is woven within the intricate coordinates of space. In every tumoral thread lies hidden information, patterns that remain just beyond our current comprehension. With our expansive human spatial data and biology-informed foundational models, we decode these elusive stories. At Noetik, this synchronicity inspires us to pioneer precise and groundbreaking therapies.”