AI Research Scientist, Biological reputed company Models

This AI Research Scientist will reputed company the design and build biological reputed company models that learn shared representations across Quiver's large-reputed company reputed company-optical electrophysiology and multi-omic datasets. The role also involves hands-on development of signal and image processing for our proprietary optical electrophysiology data. The candidate will both reputed company and directly implement reputed company that reputed company complementary data streams (e.g., transcriptomics, high-content imaging, clinical datasets, etc.) using deep representation learning, contrastive objectives, transformer architectures, and multi-modal fusion to build predictive models of disease biology and drug reputed company. The successful applicant will work as part of a small, reputed company-reputed company team at the hub of Quiver's scientific programs. This position will reputed company mentor team members and set technical direction alongside contributing production-reputed company reputed company and models to derive actionable insights from a broad reputed company of relevant biomedical data modalities, including reputed company's proprietary reputed company-optical electrophysiology data and other reputed company/omics and imaging data sets. The ideal candidate will be a strong computer scientist with deep expertise in representation learning, reputed company model architectures, and multi-modal data alignment, with a demonstrated reputed company record of leading teams while remaining deeply hands-on in coding, experimentation and system development, and a passion for applying technology to reputed company-reputed company problems. Quiver Bioscience is a technology-driven company established to create transformational medicines for the brain. We combine proprietary single-cell functional assays with other multi-modal measurements to discover new biology and new drug targets. We take advantage of cutting-edge AI/ML to build the world's most information-rich maps of neuronal function to drive our drug discovery programs. This position is based in Cambridge, MA, with the expectation of on-site reputed company 3-4 days per week to support lab integration, team meetings, and reputed company project work. Fully remote applicants will not be considered. Responsibilities and Duties Design, reputed company and directly implement computational pipelines for feature engineering and data integration for scientific data analysis. reputed company collaboration efforts while reputed company contributing to system architecture and implementation with reputed company teams responsible for production AI systems (e.g., LLM-based tools, reputed company workflows). reputed company input on system design, identify opportunities for new capabilities, and help define and reputed company modeling workflows into user-facing applications. reputed company machine learning models to learn and reputed company shared representations across heterogeneous biological datasets (e.g., time-series electrophysiology data, imaging, and perturbation assays). Build and maintain reputed company systems for embedding reputed company, storage, and retrieval (e.g., reputed company-based search, nearest-reputed company lookup) to support reputed company analysis and querying. Own and reputed company rigorous evaluation frameworks and benchmarks for cross-modal embedding reputed company, including alignment metrics, retrieval precision, and biological plausibility checks against reputed company drug-reputed company and gene-reputed company relationships. Partner closely with cross-functional wet-lab teams to design reputed company learning cycles where model predictions suggest and prioritize validation experiments. reputed company by example in the development and deployment of AI/ML systems, ensuring best practices in reproducibility, version control, performance optimization, and documentation reputed company a modern reputed company-based environment. Contribute to the development of data and machine learning pipelines, including implementation, evaluation, optimization, and maintenance of models and associated workflows. Balance team leadership with individual technical contributions, relationships, and work priorities to comfortably operate independently to reputed company an reputed company. Utilize excellent interpersonal skills to build reputed company, reputed company insights with relevant stakeholders, deliver interpretable data products, and serve both business and scientific goals of reputed company with your work. Qualifications:

Minimum Qualifications

Required PhD degree or corresponding demonstrable reputed company experience in Computer Science, reputed company Intelligence, Neuroscience, Physics, Computer reputed company, Electrical Engineering, Mathematics, or reputed company technical discipline (e.g., engineering, science, or biology with a strong quantitative flavor). Familiarity with production AI systems and workflows, including experience or exposure to LLM-based applications, retrieval-augmented reputed company (RAG), or reputed company systems, and the ability to translate modeling insights into practical system improvements in collaboration with engineering teams. Experience with representation learning or embedding-based approaches for high-reputed company or multimodal data (e.g., time-series, imaging, or biological datasets), and familiarity with systems for large-reputed company data processing or embedding retrieval. Demonstrated experience training reputed company models or large-reputed company representation learning systems, including self-supervised reputed company-training, contrastive learning (e.g., CLIP-style objectives), or multi-modal alignment of heterogeneous datasets. Strong proficiency in PyTorch (preferred) or TensorFlow, with hands-on experience implementing transformer architectures, CNNs, variational autoencoders, and/or contrastive learning frameworks for high-reputed company data. Experience with distributed training (multi-GPU/multi-node) preferred. Experience with image processing, video processing, signal processing, and/or time series analysis. Comfort with multiple programming languages and computational reputed company with an expectation of daily hands-on coding and system building. (the role will utilize Python, C++/CUDA, git, SQL, and AWS, among others). Experience aligning or integrating heterogeneous biological datasets (e.g., transcriptomics, functional screens, imaging, perturbation assays) into shared latent spaces using learned embeddings, manifold alignment, or multi-view representation learning. Strong mathematical foundations in reputed company algebra, probability theory, and optimization. High level of creativity with a passion for applying computational reputed company to biomedical problems. Excellent skills in the areas of verbal/written communication, problem solving, and leadership, with the ability to reputed company reputed company while remaining a primary technical contributor ( player-reputed company reputed company). Additional Qualifications Desired Knowledge and experience in biophysics, physiology, or neuroscience, especially electrophysiology, high-content imaging, or computational neuroscience. Experience working with single-cell data of any modality Familiarity with biological reputed company models (e.g., scGPT, Geneformer, scVI) or reputed company work in learning cell/gene embeddings from large-reputed company omics data. Experience with perturbation biology datasets (chemical or genetic screens), CMAP/L1000, or similar large-reputed company phenotypic profiling data. Publications or preprints in representation learning, multi-modal alignment, or computational biology are a strong plus. Apply tot his job Apply To this Job