TechBio’s next generation

We are doctors, scientists, engineers, machine learning researchers, computational biologists, with a shared vision to discover precision cancer immunotherapies to impact the lives of patients and their families.

Ron W. Alfa, MD, PhD

Co-Founder, CEO

Salt Lake City, UT

Ron W. Alfa, MD, PhD

Co-Founder, CEO

Salt Lake City, UT

Ron W. Alfa, MD, PhD

Co-Founder, CEO

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."

Jacob Rinaldi, PhD

Co-Founder, CSO

San Francisco, CA

Jacob Rinaldi, PhD

Co-Founder, CSO

San Francisco, CA

Jacob Rinaldi, PhD

Co-Founder, CSO

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."

Lacey Padrón, PhD

Chief Technology Officer

Boulder, CO

Lacey Padrón, PhD

Chief Technology Officer

Boulder, CO

Lacey Padrón, PhD

Chief Technology Officer

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.”

Daniel Bear, PhD

Director of AI Research

Cambridge, MA

Daniel Bear, PhD

Director of AI Research

Cambridge, MA

Daniel Bear, PhD

Director of AI Research

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."

Dexter Antonio

Senior Data Scientist

San Francisco, CA

Dexter Antonio

Senior Data Scientist

San Francisco, CA

Dexter Antonio

Senior Data Scientist

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.”

Eric Siefkas

Senior Software Engineer

Loveland, CO

Eric Siefkas

Senior Software Engineer

Loveland, CO

Eric Siefkas

Senior Software Engineer

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."

Eshed Margalit, PhD

Machine Learning Scientist

San Francisco, CA

Eshed Margalit, PhD

Machine Learning Scientist

San Francisco, CA

Eshed Margalit, PhD

Machine Learning Scientist

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."

Francis Fernandez

Associate Scientist

San Francisco, CA

Francis Fernandez

Associate Scientist

San Francisco, CA

Francis Fernandez

Associate Scientist

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.”

Hargita Kaplan

Director of Multimodal Tissue Profiling

San Francisco, CA

Hargita Kaplan

Director of Multimodal Tissue Profiling

San Francisco, CA

Hargita Kaplan

Director of Multimodal Tissue Profiling

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.”

Jake Schmidt

Machine Learning Engineer

Salt Lake City, UT

Jake Schmidt

Machine Learning Engineer

Salt Lake City, UT

Jake Schmidt

Machine Learning Engineer

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.”

Joy Tea, PhD

Director of Biomarker Operations

San Francisco, CA

Joy Tea, PhD

Director of Biomarker Operations

San Francisco, CA

Joy Tea, PhD

Director of Biomarker Operations

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.”

Kelsey Dutton

Senior Software Engineer

Boulder, CO

Kelsey Dutton

Senior Software Engineer

Boulder, CO

Kelsey Dutton

Senior Software Engineer

Before Noetik:

Enterprise software engineer, focused on security and authentication, specializing in backend development and building modular systems on serverless infrastructure. Spanning from client-facing to standing up data pipelines.

Why Noetik:

“The opportunity to get in on the ground floor of an exciting company in a new (to me) space of biotech was deeply appealing. The work in biotech is tangible both in the day-to-day and in the eventual impact in a way none of my previous roles have been.”

Lucas Cavalcante, PhD

Data Scientist

San Francisco, CA

Lucas Cavalcante, PhD

Data Scientist

San Francisco, CA

Lucas Cavalcante, PhD

Data Scientist

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.”

Maxime Dhainaut, PhD

Director, Spatial Functional Genomics

New York, NY

Maxime Dhainaut, PhD

Director, Spatial Functional Genomics

New York, NY

Maxime Dhainaut, PhD

Director, Spatial Functional Genomics

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."

Meena Subramanian, PhD

Principal Computational Biologist

San Francisco, CA

Meena Subramanian, PhD

Principal Computational Biologist

San Francisco, CA

Meena Subramanian, PhD

Principal Computational Biologist

Before Noetik:

Founder of Dropprint Genomics (acquired by Immunai); Y Combinator alum; PhD in Bioinformatics.

Why Noetik:

“Noetik is pushing the boundary on collecting and interrogating high resolution spatial data. It’s unique and exciting.”

Nicole Snell, PhD

Chief of Staff

Columbia, MD

Nicole Snell, PhD

Chief of Staff

Columbia, MD

Nicole Snell, PhD

Chief of Staff

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.”

Rodney Collins, PhD

Scientist

San Francisco, CA

Rodney Collins, PhD

Scientist

San Francisco, CA

Rodney Collins, PhD

Scientist

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.”

Tyler Van Hensbergen

Senior Software Engineer

Portland, OR

Tyler Van Hensbergen

Senior Software Engineer

Portland, OR

Tyler Van Hensbergen

Senior Software Engineer

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.”

Yu (Phoebe) Guo, PhD

Senior Computational Scientist

San Francisco, CA

Yu (Phoebe) Guo, PhD

Senior Computational Scientist

San Francisco, CA

Yu (Phoebe) Guo, PhD

Senior Computational Scientist

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. "

Yubin Xie, PhD

Machine Learning Scientist

New York, NY

Yubin Xie, PhD

Machine Learning Scientist

New York, NY

Yubin Xie, PhD

Machine Learning Scientist

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.”