Scientist - Human-Computer Interaction (UX/HCI/HMI)

Charles River Analytics, a proud member of the GRVTY family, is dedicated to developing innovative solutions and cutting-edge technology to address some of the world’s most pressing challenges. Our dynamic team of tech entrepreneurs collaborates to lead advancements in artificial intelligence, robotics, smart sensing, and human-centered computing. Our resear…

Korrobio seeks an Associate Scientist to join its Compound Management, Cell Screening, and NGS teams at 60 First St, Cambridge, MA 02141. This position supports key research activities and collaborates with scientists across several disciplines. Main responsibilities Support daily compound management tasks and keep detailed records of inventory and usage. Assist with cell screening workflows, ensuring accuracy and consistency in experiments. Contribute to Next Generation Sequencing (NGS) projects, helping maintain efficient and reliable processes. Collaboration This role involves close teamwork with scientists from multiple research areas. Careful handling of compounds, execution of cell-based assays, and participation in sequencing efforts all help advance ongoing projects.

About Lila Sciences Lila Sciences stands at the forefront of innovation with the world's first scientific superintelligence platform and autonomous laboratory dedicated to life sciences, chemistry, and materials science. Our mission is to revolutionize scientific discovery, leveraging AI to enhance every facet of the scientific method. By introducing scientific superintelligence, we aim to address humanity's most pressing challenges while accelerating advancements in human health, climate, and sustainability. Discover more about our vision at www.lila.ai. If you resonate with our mission and possess some of the qualifications listed below, we invite you to apply and join our dynamic team. Your Role and Impact at Lila As a Robotics Scientist at Lila, you will spearhead the research and development of autonomous robotic systems that constitute the intelligent backbone of our scientific superintelligence platform. Your innovations in novel algorithms and intelligent robotic solutions will enable seamless interactions between robotic systems and human scientists, driving fully autonomous workflows for groundbreaking scientific discovery. You will integrate cutting-edge robotics, machine learning, and systems engineering into your work, fostering a new era of scientific exploration. Your Contributions Will Include Designing and developing autonomous robotic systems for transport and workcell operations, incorporating sophisticated path planning, navigation, and motion planning algorithms. Creating production-level mobile manipulation platforms utilizing ROS/ROS2 and modular robotic architectures. Enhancing robotic perception by integrating diverse sensing modalities, including 3D vision, LIDAR, and tactile sensors, to facilitate robust and adaptable task execution. Employing simulation environments to model, test, and optimize task planning, scheduling, and robot behaviors across varied lab scenarios. Collaborating with AI, mechanical, and software engineering teams to transform theoretical robotics research into practical autonomous systems. What You Will Need to Succeed A Ph.D. in Robotics, Computer Science, Mechanical or Electrical Engineering, or a closely related field, or equivalent research experience. In-depth expertise in motion planning, path planning, and navigation for both manipulation and mobile robotics. Proficient in ROS/ROS2, C++, and Python, with practical experience in constructing robotic systems for real-world applications. Comprehensive understanding of perception systems and sensor integration, including cameras, LIDAR, and tactile sensors.

Your Role at Lila Sciences As a key contributor to our Physical Sciences division, you will focus on advancing the field of in silico materials discovery techniques. Your responsibilities will involve designing autonomous workflows and data-driven pipelines that effectively integrate simulation with artificial intelligence. You will lead the development of strategies that empower agents to analyze simulation data, derive hidden insights, and facilitate hypothesis generation and materials design. Your innovative approach will enhance our utilization of simulation outputs for discovery, fostering a seamless integration of physics-based modeling with AI reasoning systems. Collaboration with specialists in simulation, AI agents, and experimental automation will be pivotal as we strive to redefine the landscape of digital discovery. Key Contributions Create cutting-edge workflows for in silico materials discovery that link physics-based simulations and generative AI models. Develop intelligent systems where AI agents autonomously design, execute, interpret, and optimize simulations. Establish frameworks that maximize the utility of simulation data for prediction, inference, and discovery, with features like automatic data extraction and model training. Prototype and assess novel paradigms for simulation-aware agents that learn from and interact with scientific simulations. Design data structures, metadata specifications, and APIs to ensure smooth information transfer among simulations, machine learning models, and experimental data repositories. Build scalable, modular workflows that connect electronic structure, atomistic, and mesoscale simulations with AI-driven reasoning and hypothesis generation. Work alongside computational scientists, machine learning professionals, and platform engineers to integrate in silico discovery pipelines into Lila’s overarching scientific superintelligence framework. Qualifications for Success PhD or equivalent experience in Computer Science, Materials Science, Chemistry, Physics, Applied Mathematics, or related fields. Strong background in in silico materials discovery, computational materials modeling, and/or simulation workflow design. Familiarity with large language models and their applications in scientific research. Experience in developing AI-driven or agentic workflows for scientific automation and discovery. Proficient programming skills in Python and scientific computing libraries.

Our MissionAt Altos Labs, our mission is to rejuvenate cell health and resilience, aiming to reverse diseases, injuries, and the associated disabilities that arise throughout life.For further details, visit our website at altoslabs.com.Our ValuesWe embrace a singular value at Altos: Everyone Owns Achieving Our Inspiring Mission.Diversity at AltosWe hold a firm belief that diverse perspectives are crucial to scientific advancement and inquiry. At Altos, outstanding scientists and industry leaders collaborate from across the globe to further our shared mission. We prioritize creating a sense of belonging, ensuring that every employee feels valued for their unique contributions. We are collectively responsible for maintaining a diverse and inclusive workplace.Your Contributions to AltosIn the role of Senior or Principal Machine Learning Scientist, you will be instrumental in the development of generative AI/ML models for multi-modal, multiscale biology, spanning from virtual cells to agentic target assessment. We seek a hands-on, innovative, and collaborative individual to join our multidisciplinary team of scientists and engineers dedicated to transforming the treatment of aging and disease. The ideal candidate will flourish in a dynamic environment that values teamwork, transparency, scientific excellence, originality, rigor, and integrity.

Your Impact at Lila Join our dynamic and innovative AI safety team at Lila Sciences, where we prioritize talent and agency to mitigate risks associated with scientific superintelligence. Our mission is to craft and execute a tailored safety strategy that aligns with our unique objectives and deployment methods. This role involves creating technical safety strategies, engaging with the broader scientific community, and producing critical technical documentation, including evaluations focused on risk and capability assessments. What You’ll Be Creating Design and implement capability evaluations to assess scientific risks, particularly from cutting-edge scientific models integrated with automated physical laboratories across biological and physical sciences. Lead and coordinate threat modeling sessions with both internal and external scientific experts, keeping abreast of emerging technologies and use cases. Develop and manage high-quality training and testing datasets for evaluations and safety systems. Analyze risks associated with Lila’s capabilities and their interactions with the broader ecosystem of general-purpose frontier models and specialized scientific tools. Contribute to high-quality research initiatives focused on scientific capability evaluation and restriction as needed. Assist with external communications regarding Lila’s safety initiatives. What You’ll Need to Succeed A PhD in biological sciences (e.g., molecular biology, virology, computational biology) or physical sciences (e.g., materials science, physics, chemistry, or chemical engineering), or similar experience. Proficient in scientific computing related to biological or physical sciences. Familiarity with dual-use research and dissemination issues within relevant safety, regulatory, and governance frameworks (e.g., export control, biological and chemical conventions). Exceptional communication skills to convey complex technical concepts to non-expert audiences effectively. Proven ability to lead internal and external teams in developing Lila's perspective on biological and physical risks. Demonstrated capacity to collaborate with cross-functional stakeholders (science, AI, product, policy) in a complex environment.

Your Contribution at Lila At Lila, we are assembling a highly skilled and proactive AI safety team that will collaborate with all core departments, including science, model training, and lab integration, to effectively address risks associated with scientific superintelligence. The primary mission of this team is to develop and execute a tailored safety strategy that aligns with Lila's unique objectives and deployment methodologies. This will encompass formulating technical safety strategies, engaging with the broader ecosystem, and producing technical documentation such as risk and capability assessments and safety measures. Your Responsibilities Establish the research and development strategy for Lila’s safety framework concerning biological and physical risks. Design and implement capability evaluations to identify scientific risks (both recognized and novel) arising from state-of-the-art scientific models integrated with automated physical laboratories across biological and physical sciences. Lead and coordinate threat modeling sessions with both internal and external scientific experts, including monitoring advancements in technologies and their applications. Create and curate high-quality training and testing datasets for evaluations and safety systems. Assess risks linked to Lila’s capabilities, considering interactions with the broader ecosystem of capabilities (including general-purpose frontier models and specialized scientific tools). Contribute to extensive, high-quality research initiatives when needed for scientific capability evaluation and restriction. Engage in external communications regarding Lila’s safety initiatives. Qualifications for Success A PhD in a biological sciences field (e.g., molecular biology, virology, computational biology) or a physical sciences field (e.g., materials science, physics, chemistry, chemical or nuclear engineering) or equivalent experience. Proven track record in setting research directions for open issues surrounding dual-use risks in biological and physical sciences. Experience in scientific computing within the biological or physical sciences. Understanding of dual-use research and dissemination issues in relation to relevant safety, regulatory, and governance frameworks (e.g., export controls, biological and chemical-related conventions). Excellent communication skills, capable of articulating complex technical concepts to non-specialist audiences. Demonstrated leadership capabilities in guiding teams of internal and external collaborators in developing Lila's perspective on biological and physical risks.

Contract Type: Full-time, PermanentLocation: Cambridge, UKVisa Sponsorship availableJoin Nu Quantum - Innovating the Future of Quantum TechnologyAt Nu Quantum, we are pioneers in the realm of quantum computing and advanced technological solutions, fueled by a passion for innovation, diversity, and excellence. We foster a collaborative environment where talented individuals from various backgrounds unite to redefine the limits of what is achievable.Founded to commercialize a decade's worth of research from the prestigious Cavendish Laboratory, Nu Quantum is dedicated to revolutionizing quantum information systems.Our team is developing groundbreaking technologies that enhance the functionality and speed of quantum computing systems. We are integrating cutting-edge quantum photonic technology to create an efficient and scalable quantum networking infrastructure in collaboration with leading corporations and academic institutions.About the RoleAs a Quantum Control Scientist in our Atomic, Molecular & Optical (AMO) team, you will bridge the gap between physics and engineering, developing and commissioning the real-time control systems that govern our internal trapped-ion quantum processing units.Your work will involve utilizing the ARTIQ platform to create a seamless orchestration of complicated hardware setups. This role encompasses designing and implementing dependable workflows for time-sensitive data acquisition and stabilization protocols, mainly using Python to interface with various systems including custom electronics, lasers, and RF hardware.We seek a creative problem-solver who thrives in a hands-on laboratory setting. Your responsibilities will include developing and optimizing real-time control software that is intricately linked with experimental instrumentation. Collaborating with physicists, engineers, and software developers will be essential, as you contribute to a high-quality, maintainable codebase while ensuring that your solutions are robust, scalable, and future-proof in our rapidly evolving organization.Key ResponsibilitiesDesign and manage real-time orchestration of experimental hardware using the open-source ARTIQ platform.Integrate and control custom hardware (e.g., electronics and FPGA boards), along with third-party hardware, primarily through Python.Monitor experimental parameters and automate their analysis to minimize manual effort and enhance repeatability.Commission, document, and train team members on both hardware and software systems.Work closely with physicists and engineers to achieve technical and performance targets.Create graphical user interfaces for experimental control, real-time monitoring, and data visualization.Collaborate with the software team to standardize workflows, adhering to best practices for maintainable and scalable code.

Your Contribution at Lila Sciences Lila Sciences is actively seeking a dedicated (Senior) Research Associate to become an integral part of our dynamic Life Sciences team. This pivotal role will be centered around the formulation of lipid nanoparticles (LNPs), their functionalization with targeting ligands, and the characterization of the resulting targeted LNPs (tLNPs). The ideal candidate will possess substantial hands-on experience in LNP formulation and characterization, bioconjugation, protein characterization, and automation technologies. Your expertise will significantly enhance our understanding of the delivery space, enabling a high-throughput closed-loop screening cascade for tLNPs. You will work collaboratively with professionals across protein, cell biology, automation, chemistry, machine learning, and data science teams to establish advanced tools for targeted nucleic acid delivery. Your Key Responsibilities Design, execute, and characterize LNP formulations utilizing various scales and mixing modalities (e.g., DLS, ribogreen, TNS). Develop and optimize high-throughput ligand conjugation and purification methodologies, leveraging automation and robotics to maximize throughput. Collaborate with cell assay and antibody experts to screen candidates across diverse tissue targets in in vivo models. Engage with chemists, biologists, engineers, and data scientists to document processes, share insights, and refine best practices in autonomous flow chemistry. Create, implement, and uphold Standard Operating Procedures (SOPs) for both existing and emerging lab processes. Your Qualifications for Success MSc in Chemical Engineering, Biomedical Engineering, Pharmaceutical Sciences, or a closely related field with 3+ years of hands-on experience in targeted LNP production or a BSc with 5+ years of relevant experience. Industry experience is highly desirable. Strong proficiency in bioanalytical techniques (e.g., DLS, fluorescence spectroscopy, electrophoresis, in vitro assays). Experience in protein and antibody design and characterization. Familiarity with automation and high-throughput workflows is preferred. Exceptional troubleshooting, communication, and collaboration skills, with a proven ability to work effectively across interdisciplinary teams. About Lila Sciences Lila Sciences is at the forefront of innovation as the world's first scientific superintelligence platform and autonomous laboratory focused on life sciences, chemistry, and materials science. We are pioneering a new era of limitless discovery by harnessing AI capabilities to enhance every facet of the scientific method. Our mission is to leverage scientific superintelligence to address humanity's most pressing challenges.

Join Lila Sciences as a Senior Research Associate or Associate Scientist in the Protein Science department, focusing on our cutting-edge Antibody Platform. You will play a crucial role in advancing our research initiatives, contributing to the development of innovative antibody-based therapeutics. This position offers the opportunity to collaborate with a talented team dedicated to scientific excellence and the pursuit of transformative solutions in healthcare.

Your Impact at Lila Sciences Join our innovative high-throughput autonomous chemistry team as a Senior Research Associate / Associate Scientist. This hands-on position bridges the fields of organic and inorganic synthesis, advanced characterization, and laboratory automation. You will design and implement high-throughput experiments, synthesize small molecules, and conduct thorough downstream analysis alongside senior scientists. Your efforts will contribute to translating ambitious product objectives into scalable experimental workflows that significantly influence our company's growth. This role provides a unique opportunity to engage with automated chemistry platforms, giving you real ownership of experiments that shape our scientific strategy and direction. Ideal candidates are execution-oriented, excel in dynamic laboratory settings, and are passionate about developing deep technical skills while making impactful contributions to the future of chemical discovery at Lila Sciences. What You’ll Be Building Independently conduct experiments for the synthesis, purification, and characterization of organic and inorganic small molecules. Optimize reactions, develop methodologies, and analyze analytical data to inform project decisions. Convert initial concepts into reliable, functional experiments. Utilize retrosynthetic analysis to assist in the synthesis of target molecules. Operate Schlenk lines, gloveboxes, and various inert-atmosphere systems for sensitive materials. Employ PAT tools (UPLC, LCMS, NMR, IR, Fluorescence, DLS) to monitor reactions, ensure quality control, and produce high-quality data for machine learning workflows. Leverage automation and AI-driven technologies to streamline workflows and reduce experimental turnaround times. Collaborate with engineers, ML scientists, and stakeholders to validate model-recommended conditions, analyze trends, troubleshoot challenges, and clearly communicate results through reports, discussions, and presentations. Maintain meticulous documentation of results, ensuring accurate digital records while adhering to EHS and laboratory best practices. What You’ll Need to Succeed M.S. in Chemistry or a related field (such as organic, organometallics, or catalysis) with a minimum of 2 years of relevant laboratory experience, or a B.S. with 5 years of experience. Hands-on experience in organic and inorganic synthesis, purification processes, chromatographic techniques, and product analysis. Strong grasp of retrosynthesis, reaction mechanisms, and method optimization workflows. Proficiency in utilizing laboratory automation tools and systems. Excellent problem-solving skills and the ability to work collaboratively in a team-oriented environment.

Join Bicycle Therapeutics, a pioneering biopharmaceutical company, as the Director of Clinical Safety Science specializing in Radiopharmaceuticals. In this critical role, you will lead the evaluation and management of clinical safety data, ensuring the highest standards of patient safety and regulatory compliance. You will collaborate closely with cross-functional teams to drive innovative solutions in our clinical development programs.

Your Impact at Lila As an ML Research Scientist specializing in Multimodal Data Extraction, you will play a pivotal role in advancing Lila's mission of achieving scientific superintelligence. Your work will focus on the development of foundational models capable of autonomously reading, interpreting, and organizing scientific knowledge from diverse formats such as text, images, and experimental data in the physical sciences. Your research will contribute to the unification of global scientific data into a machine-readable format, enhancing reasoning, prediction, and autonomous discovery within materials science and chemistry. What You Will Be Building Innovate and create AI systems that effectively extract and organize knowledge from a variety of scientific resources. Design and optimize large language models, multimodal models, and specialized architectures for accurate and interpretable data extraction. Develop scalable solutions for managing unstructured and heterogeneous scientific data, integrating various formats including text, tables, and visuals. Collaborate with subject matter experts to ensure that the extracted data aligns with real-world research workflows. Publish impactful research that propels the field of multimodal understanding and AI-driven knowledge extraction forward.