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SVP, Head of Research at Recursion (RXRX), Early employee from Seed through IPO. Stanford University M.D, Ph.D in Neuroscience.
"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."
VP of Informatics at Parker Institute for Cancer Immunotherapy; startup experience applying data science to biology across domains; Cancer survivor.
“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.”
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.
"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."
10+ years oncology/immunotherapy drug discovery and development in pharma and biotech including Roche Switzerland and Boehringer-Ingelheim. Led teams and programs from target discovery to Phase 1 clinical trials. Academic background in cell biology, virology, T cell immunology. Assistant Professor, MD Anderson Cancer Center. Postdoc, UC Berkeley/Memorial Sloan Kettering Cancer Center. PhD, Johns Hopkins University School of Medicine.
“Noetik’s data collection and AI approaches are the future of medicine. The technology can pinpoint complex, causal patient biology and match this with the right therapeutic intervention. This will transform cancer drug development and treatment for benefit of patients in need.”
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.
"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."
Chief People Officer who helped start and grow Lyell Immunopharma, scaling from ~20 to over 300 and through a successful 2021 IPO. Spent a decade at Genentech and Roche in local and global HR leadership roles spanning Technical Operations, Product Development, Clinical Operations, and US Commercial - with a Chief of Staff stint in US Virology. Certified Executive & 360 Feedback Coach, and a life-long adventurer who’s just as energized by people strategy and cutting-edge biotech as by global travel adventures.
"Noetik is at the forefront of AI-powered biotech innovation, and I felt an immediate connection to both the mission and the people. What inspires me as much as the mission, is that their drive to break barriers goes beyond science and cancer research—it’s also reflected in how they are shaping culture and people practices. I’m thrilled to be part of this team and its mission."
Five years of experience as an engineer, working across DevOps, Data Engineering, and Backend development. Previously worked at a FinTech startup, focusing on cloud infrastructure and data pipelines, and later at a Healthcare startup, where I contributed to MRI imaging and MLOps.
"Noetik’s ambitious goal to train AI for the purpose of fighting cancer drew me in, particularly because of the unique data challenges it involves. There is an abundance of data in the healthcare space, and it's often messy, fragmented, and unstructured. The opportunity to work with this data, combine it in new ways, and support the development of artificial intelligence that can simulate cell biology and improve patient outcomes is incredibly exciting."
Mostly recently worked for a few years doing ML engineering at Dyno Therapeutics, improving capsid delivery through protein engineering. Prior to that, spent another few years doing ML research at Anthem (now Elevance Health), building better multimorbidity risk scores. Before that, did some ML research work in cancer medical imaging and photoplethysmogram analysis.
"It's rare that an AI biotech startup simultaneously has an extremely useful set of data that is hard to replicate, the computational expertise to use it, and the business sense to understand where best to rely on it. Noetik has all three."
Experience in managing day-to-day operations, implementing innovative technologies, and ensuring operational efficiency. Before joining Noetik, I led various projects aimed at optimizing lab performance and integrating advanced technologies.
“I chose to work at Noetik because of its innovative approach to developing precision cancer therapies using AI and machine learning. With my background in lab operation management, I’m eager to contribute to Noetik’s mission and support its goals.”
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.
"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."
Previously worked as a Machine Learning Scientist at Cellarity, designing and analyzing large-scale single-cell perturbation datasets. Before that, MS/BS in Mathematics at Yale.
"I believe that recent developments in AI and spatial technology will bring about the future of cancer immunotherapy, and that Noetik is best poised to usher in that future. I was drawn to Noetik by the prospect of being part of such a talented, hard-working, and collaborative team working towards this ambitious goal."
Eight years building experimental and computational pipelines to generate, process, and analyze multimodal biological data at industrial scale. Most recently, founding computational scientist at a spatial biology startup. Ph.D. in Neuroscience from Harvard University and B.A./M.S. in Neuroscience from Johns Hopkins University.
"Capturing the complexity of human diseases requires generating massive datasets of high-dimensional, multimodal spatial biology measurements. In turn, distilling that complexity down to the fundamental mechanisms requires artificial intelligence, particularly self-supervised learning. The team at Noetik recognized that the requisite technologies are just now coming of age and can deliver on the potential to create transformative therapies for patients."
With over four years of research experience, Derrick possesses extensive technical expertise in Molecular Biology and Immunohistochemical assays. At Cornell University, Derrick spearheaded the histological characterization of mouse cancer models. Furthermore, he developed bacterial cell lines for molecule expression and in vivo colonization within microbial systems.
"I am deeply enthusiastic about contributing to advanced cancer research. Noetik stands at the vanguard of cancer research, uniquely positioned at the nexus of sophisticated biomedical science and potent machine learning models. I am sincerely appreciative of the opportunity to collaborate with exceptionally experienced and knowledgeable researchers in their respective domains."
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.
“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 joining Noetik, spent nearly a decade advancing histology and biomarker discovery across academic, biotech, and clinical settings. Developed multiplex-IF panels, spatial transcriptomic workflows, and image analysis pipelines to support translational research in oncology and neuroscience. Most recently, developed RNA and protein-based assays at Arcus Biosciences to better understand tumor biology.
"I chose to join Noetik because it sits at the intersection of cutting-edge science and thoughtful innovation. The company’s focus on integrating high-quality tissue analysis with meaningful computational insights aligns perfectly with my passion for histology and data-driven discovery. Beyond the science, I was drawn to the collaborative culture and the opportunity to help shape a growing team with a shared mission"
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.
"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."
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.
"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."
Worked in clinical and research labs for 15 years across a variety of experiments.
“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.”
Brings a multidisciplinary background in biochemistry, regenerative medicine, and software engineering to his role at Noetik. After earning a bachelor's degree in Biochemistry and completing several years of medical school, he conducted research on hematopoietic stem cells at the Forsberg Lab and the California Institute for Regenerative Medicine. His career has since spanned a range of biotech and tech-bio companies, contributing to efforts from early discovery through to the clinic.
"I was drawn to Noetik for its machine learning–first approach to pressing biomedical problems, the excellence of the team, and the richness of the data. It’s a thrilling opportunity to see how quickly we can make a meaningful difference in the lives of patients and their loved ones."
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.
“I believe in the potential of immune therapy to improve patient outcomes and the power of machine learning to improve drug discovery.”
PhD from Stanford and spent 11 years at Genentech. Experienced preclinical researcher in neuroscience and biomarker operations in cancer immunotherapy.
“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.”
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.
"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!"
Bioinformatics Scientist/Engineer at TRexBio where he used multiomic single cell data for data pipelines, target discovery, and program data package support. PhD in Bioinformatics, MS is Biostatistics, and BS in Immunology from UC Davis and UCLA where he worked in the Bioinformatics Core handling a plethora of client projects, instructing courses, and was a lead in the NeuroMabSeq project for hybridoma sequencing and dissemination
"After working in the autoimmunity space, I am very interested in further experience in the oncology space and the spatial modality specialization at Noetik is extremely promising and exciting. Noetik is a fantastic collaboration across extremely passionate and talented immunologists, data scientists, and engineers and it is moving to be a part of such a well rounded group."
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.
“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.”
Since earning a PhD in Computer Science, spent the last few years designing and deploying AI systems that extract meaningful insights from complex images and multi-modal data. Focused on applying deep learning to streamline workflows in life science domains, where transferability and precision matter. Built scalable cloud-based ML pipelines, from model development to production deployment, and led projects that directly improved efficiency, reduced manual labor, and revealed patterns that weren’t visible to the human eye. Motivated by work that bridges ML with real-world impact, and eager to bring that experience to Noetik’s mission.
"What draws me to Noetik is its mission at the intersection of deep tech and real-world impact. Noetik isn’t just building foundation models for cancer biology, it’s using them to uncover insights that were previously inaccessible, fundamentally transforming how we understand and treat cancer. I’m excited about the opportunity to contribute to that vision and help scale the AI systems that make this kind of biological discovery possible."
Postdoctoral research at Icahn School of Medicine focused on immuno-oncology; Associate Director of Early Discovery at ImmunAI.
"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."
PhD in computer science at Cornell University, where she studied algorithms & AI and worked on computational models contact tracing.
"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."
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.
“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.”
Graduated with an MS in Biotechnology from Johns Hopkins and have since built a career at the intersection of gene and cell therapy, translational research, and spatial biology. Spent a lot of time developing ocular and CNS disease models, designing molecular and cellular assays, and making sure experiments produce data that’s actually interpretable. Along the way, supported preclinical and IND-enabling studies and learned how to turn ambitious biological questions into reproducible science.
“I’m obsessed with high-dimensional biological data, and even more obsessed with making sense of it. After years of generating molecular and spatial datasets, I was excited by Noetik’s approach to combining deep biology with machine learning to uncover patterns you wouldn’t find by eyeballing a heatmap. Getting to work with a team that enjoys thinking deeply, asking hard questions, and building tools that actually move the science forward makes this a fun place to be!
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.
"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."
Pathology lab manager with extensive experience and clinical expertise. Time spent with several startups, Gladstone Institutes, and UCSF.
“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.”
Data Science leadership at Apple, with a focus on causal inference and media services; Senior Data Scientist at Stitch Fix, with a focus on ML model integration; Miller Fellowship at UC Berkeley with the department of Molecular and Cell Biology; PhD in Neuroscience from the University of California, San Francisco with an emphasis on olfaction; BS in Biology from the University of Oregon.
“Leveraging AI technologies for tumor understanding will be fantastically difficult—and fantastically important. I'm excited to be joining a team with the ability and the experience to deliver on this mission, and to benefit countless lives in the process.”
Worked as a software engineer at AWS, Uber, and startups, specializing in distributed systems, cloud infrastructure, MLOps, and LLM technologies.
"Joined Noetik because its mission of leveraging AI to address biotech and pharmaceutical challenges is both innovative and deeply compelling."
Most recently, Senior Director of Data Science and Lead Discovery at Enceladus Bio, developing novel gene editors. Previously, developed cancer therapeutic response predictors as Director of Data Science at Notable Labs and created polygenic risk score model products for Type 2 Diabetes and Hypertension at 23andMe. Stanford University M.D., Ph.D. in Biology
"I believe that the most efficient way to cure cancer is to match the right drug to each patient. AI enables this goal. Execution requires a true interdisciplinary team like Noetik, where the nuances of biology are carefully considered alongside the AI."
Nine years of experience leading and scaling biospecimen operations in fast-paced early stage biotech environments. I helped scale operations at Invitae (now Labcorp) and was part of the founding scientific operations team at Freenome, partnering cross-functionally to support growing research and clinical programs. I’m driven by building teams and infrastructure that allow science to move faster and with purpose.
"Noetik’s mission to learn directly from human tumors and use AI to match the right drugs to the right patients deeply resonates with me, because it tackles one of the hardest and most meaningful challenges in cancer care. There is a genuine sense of momentum and purpose building at Noetik. Being part of that exciting energy—while working alongside some of the brightest minds in the industry—is what truly drew me to 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.
“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.”
Investor, Life Sciences at Khosla Ventures; EIR/Analyst at EcoR1 Capital; R&D at Repertoire Immune Medicine; Postdoc from UMass Medical School and Harvard; PhD from VCU; BSc from Université de Rennes 1 (France).
"Most therapies fail because they don’t account for the biological complexity unique to each patient. Noetik starts where it matters most (real-world human samples + data) and has built a cutting-edge spatial, multimodal AI stack to capture that complexity. Noetik is creating a foundation model to transform how therapies are precisely tailored to individuals. Joining this uniquely talented team means being part of creating real, transformative impact on patients' lives."
