Current openings at Arc Institute

About Arc Institute The Arc Institute is a new scientific institution conducting curiosity-driven basic science and technology development to understand and treat complex human diseases. Headquartered in Palo Alto, California, Arc is an independent research organization founded on the belief that many important research programs will be enabled by new institutional models. Arc operates in partnership with Stanford University, UCSF, and UC Berkeley. While the prevailing university research model has yielded many tremendous successes, we believe in the importance of institutional experimentation as a way to make progress. These include: Funding: Arc fully funds Core Investigators’ (PIs’) research groups, liberating scientists from the typical constraints of project-based external grants. Technology: Biomedical research has become increasingly dependent on complex tooling. Arc Technology Centers develop, optimize, and deploy rapidly advancing experimental and computational technologies in collaboration with Core Investigators.  Support: Arc aims to provide first-class support—operationally, financially, and scientifically—that will enable scientists to pursue long-term high risk, high reward research that can meaningfully advance progress in disease cures, including neurodegeneration, cancer, and immune dysfunction. Culture: We believe that culture matters enormously in science and that excellence is difficult to sustain. We aim to create a culture that is focused on scientific curiosity, a deep commitment to truth, broad ambition, and selfless collaboration. Arc has scaled to over 350 people to date. With $650M+ in committed funding and a state of the art new lab facility in Palo Alto, Arc will continue to grow quickly in the coming years. About the position The Jain Lab is looking for motivated, hard-working and curious applicants. At a high level, we study how organisms interact with their environments – how “what we breathe” and “what we eat” affects our metabolism and disease progression. More specifically, we are focused on oxygen and vitamin/cofactor metabolism. We recently discovered that chronic hypoxia (equivalent to living in the mountains of Peru or Nepal) can serve as a therapy for mitochondrial disease. This approach is currently in clinical trials. This work has inspired a broader set of research directions ranging from fundamental biochemistry to animal physiology. The questions we ask: How do cells and organisms sense oxygen or vitamin levels? Are there novel oxygen sensors and vitamin sensors to be found? How does the body adapt to variations in oxygen levels? Or vitamin levels? When the supply and demand of oxygen or vitamins becomes mismatched, how does this contribute to disease? Can we “turn the oxygen and vitamin dials” as creative new therapies? What is the most practical form of turning these concepts into translatable therapies? The approach we take: CRISPR screens, metabolomics, classical biochemistry/molecular biology, animal physiology and beyond. Post-docs will be encouraged to lead independent projects resulting in high impact publications, present at conferences and prepare for long-term careers in academia or industry. About you You are extremely curious and self-motivated to push the boundaries of biomedical research. You thrive in a fast-paced environment while conducting rigorous and impactful research. You are intellectually independent and are able to design new research directions and projects (with input from your PI). You are eager to learn and adapt new techniques. You are excited by solving puzzles that have a translational impact.  In this position you will Find new functions for enzymes or cofactors (vitamins) Contribute to our molecular understanding of how key metabolites are sensed by the body. Develop novel therapeutic strategies for nutrient-based therapies. Collaborate with post-docs and students to understand how enzymes and metabolites interact for key biochemical functions. Publish, present, and represent that lab in journals and conferences. Present at lab meetings, and participate in Arc-wide activities (seminars, symposiums, etc). Requirements PhD in metabolism, animal physiology, molecular biology, biochemistry, genomics, or related field  Excellent written and verbal communication skills. Demonstrated ability to work in a fast-paced environment and be both an independent thinker and a highly collaborative team player. The minimum base salary for this position is $80,000. Base salary for this role is determined by how many months of relevant postdoctoral experience a successful candidate has. Base salary for this role is not negotiable.

About Arc Institute The Arc Institute is a new scientific institution that conducts curiosity-driven basic science and technology development to understand and treat complex human diseases. Headquartered in Palo Alto, California, Arc is an independent research organization founded on the belief that many important research programs will be enabled by new institutional models. Arc operates in partnership with Stanford University, UCSF, and UC Berkeley. While the prevailing university research model has yielded many tremendous successes, we believe in the importance of institutional experimentation as a way to make progress. These include: Funding: Arc will fully fund Core Investigators’ (PIs’) research groups, liberating scientists from the typical constraints of project-based external grants. Technology: Biomedical research has become increasingly dependent on complex tooling. Arc Technology Centers develop, optimize and deploy rapidly advancing experimental and computational technologies in collaboration with Core Investigators.  Support: Arc aims to provide first-class support—operationally, financially and scientifically—that will enable scientists to pursue long-term high risk, high reward research that can meaningfully advance progress in disease cures, including neurodegeneration, cancer, and immune dysfunction. Culture: We believe that culture matters enormously in science and that excellence is difficult to sustain. We aim to create a culture that is focused on scientific curiosity, a deep commitment to truth, broad ambition, and selfless collaboration. Arc has scaled to over 350 people to date. With $650M+ in committed funding and a state of the art new lab facility in Palo Alto, Arc will continue to grow quickly in the coming years. About the Position We are searching for an exceptional scientific leader to establish a new team within Arc Institute’s Computational Technology Center, serving as the Director, Machine Learning for our Alzheimer's Disease Initiative (ADI).  This ambitious initiative spans Arc's Technology Centers and Core Investigator Laboratories and focuses on high-throughput interrogation of neurodegeneration and Alzheimer's disease mechanisms using advanced gene editing and functional genomics approaches. As the Machine Learning Research Lead, ADI, you will spearhead development of sophisticated machine learning foundation models to capture cell states and infer gene regulatory networks and causal relationships to predict therapeutic interventions. This position offers the rare opportunity to build and lead a world-class team while making direct contributions to understanding and potentially treating Alzheimer's disease through state-of-the-art computational biology and machine learning approaches. About You You are passionate about machine learning and computational biology, with expertise in applying cutting edge ML approaches to biological systems You excel at developing interpretable machine learning approaches, such as variational inference and causal modeling methods You are excited about building and leading a technical team while remaining hands-on with foundation model development and implementation.  You thrive in collaborative, multidisciplinary environments and enjoy working with both computational scientists and wet lab biologists You are a continuous learner who stays current with the latest developments, in both machine learning and neuroscience In This Position, You Will Attract, build and lead a team of exceptional machine learning research scientists dedicated to developing foundation models for cellular systems in Alzheimer's disease Develop and execute on a roadmap of interpretable machine learning approaches to understand disease mechanisms, with emphasis on variational inference, causal modeling, as well as modern transformer- and diffusion-based architectures Work closely with experimentalists on brain organoid/spheroid cellular models as well as in vivo models, working with scRNA-seq, Perturb-seq and other datasets to unravel causal gene pathways relevant to Alzheimer’s disease Develop predictive modeling approaches to identify how perturbations can move cell states from high risk Alzheimer’s profiles back to healthy / low risk states Collaborate closely with experimental biologists to ensure ML models are grounded in disease biology and can feedback into future experimental strategies Foster collaborations with external partners in the computational biology and neuroscience communities Publish high-impact research through preprints, journal publications, open source code, and presentations at leading conferences Required Qualifications PhD in Computational Biology, Bioinformatics, Machine Learning, Computer Science, or related quantitative field 7+ years of relevant experience with a minimum of 3 years of people management experience Strong research background with experience in academic settings (university, research institute) and/or biotech/pharmaceutical industry with a focus on scientific innovation Proven expertise in machine learning applications to biological datasets, with specific experience in single-cell profiling data and foundation model development Deep experience with interpretable machine learning approaches for biological systems (e.g. variational inference methods). Advanced technical skills in machine learning frameworks, particularly PyTorch, and ideally experience with model training at scale Publications in top-tier journals in computational biology and machine learning Excellent communication skills with ability to present complex machine learning concepts to both computational and biological audiences Proven ability to remain technically hands-on while providing effective team leadership, mentorship, and management Background in neurodegeneration research including familiarity with Alzheimer's disease datasets, pathways, networks, disease mechanisms, and eQTL analysis is a plus  The base salary range for this position is $338,500 to $400,500. These amounts reflect the range of base salary that the Institute reasonably would expect to pay a new hire or internal candidate for this position. The actual base compensation paid to any individual for this position may vary depending on factors such as experience, market conditions, education/training, skill level, and whether the compensation is internally equitable, and does not include bonuses, commissions, differential pay, other forms of compensation, or benefits. This position is also eligible to receive an annual discretionary bonus, with the amount dependent on individual and institute performance factors.

About Arc Institute The Arc Institute is a new scientific institution that conducts curiosity-driven basic science and technology development to understand and treat complex human diseases. Headquartered in Palo Alto, California, Arc is an independent research organization founded on the belief that many important research programs will be enabled by new institutional models. Arc operates in partnership with Stanford University, UCSF, and UC Berkeley. While the prevailing university research model has yielded many tremendous successes, we believe in the importance of institutional experimentation as a way to make progress. These include: Funding: Arc will fully fund Core Investigators’ (PIs’) research groups, liberating scientists from the typical constraints of project-based external grants. Technology: Biomedical research has become increasingly dependent on complex tooling. Arc Technology Centers develop, optimize and deploy rapidly advancing experimental and computational technologies in collaboration with Core Investigators.  Support: Arc aims to provide first-class support—operationally, financially and scientifically—that will enable scientists to pursue long-term high risk, high reward research that can meaningfully advance progress in disease cures, including neurodegeneration, cancer, and immune dysfunction. Culture: We believe that culture matters enormously in science and that excellence is difficult to sustain. We aim to create a culture that is focused on scientific curiosity, a deep commitment to truth, broad ambition, and selfless collaboration. Arc has scaled to over 350 people to date. With $650M+ in committed funding and a state of the art new lab facility in Palo Alto, Arc will continue to grow quickly in the coming years. About the position We are looking for an exceptional experienced machine learning scientist specializing in developing large-scale models. The ideal candidate will play a key role in constructing advanced machine learning models to predict cell state response to perturbations as part of Arc’s Virtual Cell Initiative. About you You are passionate about machine learning with real-world applications and scientific impact. You want to develop cutting-edge, biology-inspired, multimodal machine learning models. You are excited about collaborating with a multidisciplinary team of experimental biologists and machine learning engineers at Arc. You are a strong communicator, capable of translating complex technical concepts to non-technical audiences across disciplines  You are a continuous learner In this position, you will Build state-of-the-art AI models for understanding how cells respond to perturbation, in collaboration with other ML researchers, engineers and experimental scientists at Arc. Guide interdisciplinary teams towards successful delivery of reliable and robust machine learning models with clear scientific impact. Stay up-to-date with the latest advancements in machine learning for computational biology, scope out new areas of work and ensure the models built at Arc remain state-of-the-art. Develop strategies for both training of models as well as the large-scale generation of new experimental data to train those models, as part of Arc’s Virtual Cell Initiative. Publish findings through journal publications, white papers, and presentations. Commit to a collaborative and inclusive team environment, sharing expertise, mentoring others and fostering collaborations. Job Requirements PhD in Computer Science, Computational Biology, Bioinformatics, Machine Learning, or a related field. Minimum of 3 years of experience post-PhD in building machine learning models for large datasets. Strong research background with contributions to machine learning conferences (e.g., NeurIPS, ICLR, ICML) or interdisciplinary scientific journals (e.g., Nature, Nature Methods, Science). Well-versed in machine learning frameworks such as PyTorch. Excellent communication skills, both written and verbal, with a strong track record of publications. Proven track record of communicating and collaborating with domain experts and ML engineers. Motivated to work in a fast-paced, ambitious, multi-disciplinary, and highly collaborative research environment. Preferred Qualifications Experience with training and scaling large-scale machine learning models. Strong foundation in software engineering with a proven ability to deliver machine learning products from research to production. Experience working with biological datasets including single-cell genomics, genomic sequences, bioimaging Demonstrated key contributions to the field of predictive modeling of cell states. The base salary range for this position is $235,000-$291,000. These amounts reflect the range of base salary that the Institute reasonably would expect to pay a new hire or internal candidate for this position. The actual base compensation paid to any individual for this position may vary depending on factors such as experience, market conditions, education/training, skill level, and whether the compensation is internally equitable, and does not include bonuses, commissions, differential pay, other forms of compensation, or benefits. This position is also eligible to receive an annual discretionary bonus, with the amount dependent on individual and institute performance factors.