Associate Scientist II

Join AECOM as a Principal Water Quality Scientist/Modeller where your expertise will contribute significantly to advancing sustainable water management solutions. In this pivotal role, you will lead projects focused on enhancing water quality, utilizing advanced modeling techniques to drive impactful results.

ABOUT PIONEERING INTELLIGENCE Pioneering Intelligence is a forward-thinking initiative that builds upon Flagship Pioneering's rich history of establishing groundbreaking scientific and computational enterprises. By leveraging cutting-edge advancements in artificial intelligence, machine learning, and data science, we aim to accelerate fundamental research and cultivate a dynamic portfolio of AI-first companies. As an integral part of Flagship's unique model that intertwines science, entrepreneurship, and investment, we transform revolutionary concepts into impactful companies, enhancing AI innovations that contribute to human health, sustainability, and more. THE ROLE We are on the lookout for a Principal Scientist specializing in Embedded Machine Learning and Computational Methods to spearhead various AI/ML and computational initiatives across early-stage ventures within our company origination framework. Your responsibilities will include defining and executing practical AI strategies, overseeing the development of methodologies and platforms (including systems design, drug design, molecular modeling, systems biology, protein design, and LLM-based workflows), and ensuring a high standard of rigor in model development, benchmarking, scaling, and reporting. You will also manage cross-functional teams as necessary, influence the strategic direction of our initiatives, and represent Pioneering Intelligence to venture teams and external collaborators. The ideal candidate is a self-motivated individual with a diverse skill set, capable of transitioning seamlessly from protein design to mass spectrometry or docking pipelines, and then creating LLM-based agents to streamline scientific workflows.

ABOUT PIONEERING INTELLIGENCEPioneering Intelligence extends Flagship Pioneering's tradition of launching innovative scientific and computational initiatives. By leveraging the latest advancements in AI, machine learning, and data analytics, we aim to expedite fundamental research and build a diverse portfolio of AI-first companies. As a key player in Flagship's integrated approach to science, entrepreneurship, and investment, we transform groundbreaking concepts into transformative enterprises that enhance AI innovations in human health, sustainability, and more.THE ROLEWe are on the lookout for a Principal Scientist specializing in Embedded Machine Learning and Computational Techniques to spearhead various AI/ML and computational initiatives across early-stage ventures in our company origination process. You will be responsible for defining and executing practical AI strategies, overseeing the development of methodologies and platforms such as systems design, drug design, molecular modeling, systems biology, protein design, and LLM-driven workflows while ensuring the utmost rigor in model development, benchmarking, scaling, and reporting. You will manage cross-functional contributors as necessary, influence the strategic direction of the company, and represent Pioneering Intelligence to venture teams and external partners. The ideal candidate is a proactive, deep thinker who can seamlessly transition between protein design one week and mass spectrometry or docking pipelines the next, while also developing LLM-based agents to automate scientific workflows.

Imagine... being part of an innovative organization that cultivates and develops life sciences companies dedicated to pioneering groundbreaking technologies aimed at revolutionizing health care and sustainability. Company Overview Expedition Medicines is a dynamic, privately held, early-stage biotechnology company at the forefront of the Protein Editing field. We specialize in creating small molecules that modify protein structure and function to target currently undruggable options across various therapeutic strategies. Our advanced platform combines cutting-edge small molecule chemistry and chemoproteomic discovery technologies with Machine Learning (ML) to facilitate generative design. Backed by Flagship Pioneering, we leverage their vision, courage, and resources to propel Expedition Medicines from platform validation to impactful patient solutions. We seek passionate, collaborative, and determined problem solvers to join our mission! Role Overview: The Senior/Principal Scientist in Structural Biology will concentrate on determining protein-ligand complex structures using X-ray crystallography and cryo-electron microscopy (cryo-EM). This role involves delivering structural insights and collaborating with project teams to advance structure-based drug design and uncover the mechanisms of action of small molecules. Key Responsibilities: Design and implement structural biology strategies for multiple projects. Oversee the design, expression, and purification of protein constructs for structural determination. Develop and execute protocols to achieve high-quality crystals for X-ray crystallography. Create and implement protocols for grid optimization, data collection, and analysis in cryo-EM. Refine and communicate structures of protein-ligand complexes, collaborating with project teams to drive hit-to-lead and lead optimization processes. Manage contract research organizations (CROs) to ensure efficient delivery of protein expression and structural biology services. Enhance our capabilities and serve as a trusted authority in the field of structural biology.

ABOUT PIONEERING INTELLIGENCE Pioneering Intelligence continues the legacy of Flagship Pioneering by creating innovative scientific and computational ventures. Utilizing advancements in AI, machine learning, and data analytics, our mission is to expedite fundamental research and establish a diverse portfolio of AI-first companies. We integrate science, entrepreneurship, and capital to transform groundbreaking concepts into impactful companies, furthering AI advancements in human health, sustainability, and more. THE ROLE We are on the lookout for a Principal Scientist in Embedded Machine Learning/Computational to spearhead multiple AI/ML and computational projects within early-stage ventures as part of Flagship’s origination process. Your responsibilities will include defining and executing effective AI strategies, leading method and platform advancements (such as systems design, drug design, molecular modeling, systems biology, protein design, and LLM/agentic workflows), and ensuring excellence in model development, benchmarking, scaling, and reporting. You'll collaborate with cross-functional teams, shape the direction of the company, and represent Pioneering Intelligence to both venture teams and external partners. The ideal candidate is a proactive deep diver, capable of transitioning from protein design to mass spectrometry or docking pipelines, and then developing LLM-based agents to streamline scientific workflows.

Your Impact at Lila Join our innovative Physical Sciences team as a Research Scientist, where you'll spearhead the development of cutting-edge generative modeling techniques to address significant challenges in materials science. Collaborate with a diverse team of machine learning experts, software engineers, and materials scientists to create and implement generative models tailored to Lila’s distinctive materials design needs. This role not only advances the forefront of scientific research but also allows you to witness the tangible impact of your work on materials being refined in our experimental facilities on a daily basis. What You’ll Be Building Generative Models: Create and deploy generative models, including Diffusion and flow-based models, alongside advanced sampling methods to solve diverse materials design challenges. Data Representation: Innovate architectures and approaches that incorporate physics-informed constraints and domain knowledge to model materials across a wide chemical space for real-world applications. Real-World Validation & Deployment: Develop and verify datasets, frameworks, and methodologies for validating generative models with experimentally realized materials. Collaborate with software engineers and product managers to implement these solutions. Cross-Functional Partnership: Engage with R&D leadership, product managers, and automation specialists to translate scientific inquiries into data requirements and modeling strategies. What You’ll Need to Succeed Proficient in Python and deep learning frameworks with experience in end-to-end workflow deployment. Familiarity with contemporary generative modeling techniques, including diffusion models and geometric deep learning, and their applications in scientific disciplines such as materials science, chemistry, and biology. A foundational understanding of materials science, physics, and chemistry, and the ability to incorporate these principles into generative model design. A self-motivated and independent thinker with keen attention to detail. Demonstrated experience in industry or notable academic achievements. Strong communication and presentation skills, with the ability to convey complex technical information effectively. Aspirations to collaborate with highly skilled teams in a dynamic, entrepreneurial, and technical environment.

Charles River Analytics, a proud member of the GRVTY family, is at the forefront of developing innovative solutions and advanced technologies designed to address some of the most challenging issues faced globally. Our dynamic team of tech entrepreneurs collaborates to enhance AI, robotics, intelligent sensing, and human-centered computing. The research and technology we develop not only propel government initiatives but also unveil new opportunities in the commercial sector. At Charles River, we take immense pride in cultivating a workplace that attracts and retains top-tier talent and creative problem-solvers in the industry. Join us as we strive to accelerate our mission-driven innovations!We are currently seeking a dedicated Senior/Principal Scientist with expertise in Human-Systems Integration, Human Factors, or Human-Computer Interaction. In this role, you will spearhead the development of cutting-edge tools and interfaces that empower users to effectively collaborate with technology in demanding environments.Your responsibilities will include leading and expanding teams of researchers, designers, and engineers to assess work domains and user needs, create novel human-AI interaction concepts, and evaluate interactive prototypes. You will also be responsible for defining and directing technical projects, while fostering robust relationships with clients, sponsors, and collaborators. As a subject matter expert in Human Systems, you will work alongside multidisciplinary teams to explore and pursue research opportunities across various technical domains.

Join SOCOTEC UK & Ireland as a Water Hygiene Team Leader in Cambridge, where you will play a pivotal role in overseeing water hygiene operations across our projects. Your leadership will ensure the highest standards of water quality and compliance with health and safety regulations. As a Team Leader, you will coordinate a dedicated team, manage project timelines, and liaise with clients to deliver exceptional service. This is an exciting opportunity for a motivated individual looking to make a significant impact in the water hygiene sector.

Harvard University is hiring a Principal Research Scientist in the Sciences - Chemistry and Chemical Biology department based in Cambridge. This position guides research activities and partners with faculty and other scientists to deepen knowledge in chemistry and chemical biology. Key responsibilities Lead research projects focused on chemistry and chemical biology topics Work with faculty and research teams to design experiments and analyze results Use new approaches to solve challenging scientific problems Support the creation of scientific papers and presentations

Join Cambridge Mobile Telematics (CMT), the largest telematics service provider globally, dedicated to enhancing road safety and improving driver behavior. Our AI-driven platform, DriveWell Fusion®, integrates sensor data from numerous IoT devices, including smartphones, connected vehicles, and dashcams, to provide actionable insights for auto insurers, automakers, and public safety organizations. With headquarters in Cambridge, MA, and offices across the globe, we are committed to making a difference for millions of drivers every day.As a Principal Machine Learning Engineer on the innovative DriveWell Atlas team, you will lead the charge in developing cutting-edge AI systems leveraging telematics data. You will spearhead projects that involve the design, pre-training, fine-tuning, and deployment of novel foundation models aimed at revolutionizing risk assessment, driver engagement, and claims processing. This role demands a profound understanding of contemporary AI methodologies, machine learning, and sensor data analysis, offering the chance to construct a pioneering large language model from petabyte-scale datasets.We seek a collaborative and inventive Principal Machine Learning Engineer who is driven by a passion for making roads safer and improving driver capabilities.

About Graphcore At Graphcore, we are pioneering the future of artificial intelligence computing. Our team comprises semiconductor, software, and AI specialists with extensive expertise in developing the complete AI compute stack—from silicon and software to large-scale infrastructure. As a proud member of the SoftBank Group, we benefit from substantial long-term investments, enabling us to contribute essential technology to the rapidly evolving SoftBank AI ecosystem. To capture the immense potential of AI, Graphcore is expanding globally, uniting the brightest minds to tackle the most challenging problems, where every individual is empowered to make a significant impact on our company, our products, and the future of AI. Job Summary As a Research Scientist at Graphcore, you will play a vital role in advancing AI research by exploring innovative ideas that address significant AI/ML challenges. The evolution of AI has been primarily driven by specialized hardware over the past decade, and we believe that developing hardware-aware AI algorithms and AI-optimized hardware will remain crucial for progress in this exciting domain. We seek candidates who are not only curious scientists but also proficient engineers, equipped with both theoretical knowledge and practical skills essential for impactful AI research. We welcome applicants with experience in low-power, edge, and embodied AI applications, including robotics, autonomous vehicles, and augmented/virtual reality. Your expertise will contribute to the training and deployment of multimodal AI models in these contexts, focusing on areas such as world models, real-time computer vision, and reasoning over audio and video streams. The Team The Graphcore Research team engages in both fundamental and applied research to define the computational needs of machine intelligence and showcase how hardware advancements can lead to the next generation of innovative AI models. We actively publish in leading AI/ML conferences (NeurIPS, ICML, ICLR) and participate in specialized workshops while collaborating with various research teams and organizations globally. We take pride in fostering a supportive and collaborative environment, where we organize ourselves around individual research interests to collectively solve challenges in domains such as efficient computation, model scaling, and distributed training and inference of AI models across multiple modalities and applications, including sequence and graph-based data. Our teams are spread across London, Cambridge, and Bristol, with projects and discussions that involve all locations.

Join us at the Toyota Research Institute (TRI) as we strive to enhance the quality of human life through innovative technologies. Our mission is to create groundbreaking tools that enrich human experiences. To spearhead this transformative evolution in mobility, we've assembled a stellar team that is pushing the boundaries in artificial intelligence, robotics, driving, and material sciences.The TeamWithin TRI's Energy and Materials division, the Future Factory team is dedicated to pioneering advanced tools and methodologies that drive flexibility and efficiency in Toyota's product design and manufacturing processes. Our goal is to expedite the journey towards an emissions-free future. We are developing comprehensive AI systems capable of reasoning through the creation of physical objects — from initial design concepts to the assembly of actual components — and building the necessary infrastructure to train and evaluate these systems on a large scale.The OpportunityWe are seeking a Research Scientist to help us build intelligent systems for physical assembly. This role is an excellent fit for recent PhD graduates with a proven track record in implementation and a deep curiosity about the manufacturing process.As a member of our research team, you will design and implement learning pipelines from the ground up, conduct experiments to assess various architectural, data, and algorithmic alternatives, and influence the application of modern machine learning to the challenges of robotic assembly. Your work will intersect policy learning, reinforcement learning, and physical reasoning, allowing you to explore the integration of large language models and agentic infrastructure in solving real-world manufacturing challenges.

Join our innovative team as a Senior Scientist where you'll drive critical research projects and make a significant impact in the field. We are seeking a highly motivated individual with a passion for scientific discovery and a strong background in relevant disciplines.

We are seeking a motivated and detail-oriented Bench Scientist to join our dynamic team in Cambridge. This entry-level position is an excellent opportunity for recent graduates or those new to the field of scientific research. As a Bench Scientist, you will play a crucial role in conducting experiments, analyzing data, and contributing to innovative projects. If you are passionate about science and eager to learn, we encourage you to apply!

Join Artech Information Systems LLC as a Scientist in Cambridge, where you will contribute to groundbreaking research and innovative solutions in a collaborative environment. Your expertise will help drive scientific advancements and enhance our projects.

Your Impact at Lila Join our team as a Machine Learning Scientist focused on pioneering multi-modal reasoning through vision-language models (VLMs) leveraging real-world scientific data, including figures, plots, and microscopy data from various sources. Your innovative designs will contribute to the advancement of Scientific Superintelligence. What You Will Be Building Lead cutting-edge research on multi-modal reasoning systems that analyze scientific data (images, plots, text, etc.) using advanced and custom VLMs. Design and implement training, adaptation, and test-time strategies (e.g., instruction tuning, supervised learning, RLHF, RAG) tailored for scientific comprehension tasks. Create datasets and benchmarks from authentic scientific artifacts (e.g., microscopy images, spectra, protocols) to evaluate model performance. Develop perception modules (e.g., OCR, table/structure recognition, plot parsing) for handling multi-modal data types. Collaborate with domain scientists and engineers to transition research into production-ready systems for enhancing scientific superintelligence. What You’ll Need to Succeed A graduate degree in a relevant discipline (Computer Science/AI, Applied Mathematics/Statistics, Electrical Engineering) or a physical sciences field (Materials, Chemistry, Physics) with a strong focus on machine learning; or equivalent research/industry experience. A proven track record in multi-modal machine learning or VLMs, evidenced by deployed systems, publications, or contributions to open-source projects. In-depth understanding of scientific QA/benchmarks and custom evaluation design. Experience with multi-modal fine-tuning, document parsing, dataset curation, and benchmarking. Robust engineering skills utilizing modern machine learning frameworks (e.g., PyTorch, Hugging Face). Strong communication and collaboration skills in cross-functional environments. Bonus Points For Experience with scientific data modalities in laboratory settings, such as microscopy images. Publications in leading ML/CV/NLP conferences or demonstrable impact in applied industrial research. Contributions to open-source multi-modal tools, evaluation suites, or datasets. About Lila Lila Sciences stands at the forefront of scientific superintelligence, operating as the world’s first platform and autonomous laboratory dedicated to life sciences, chemistry, and materials science. We are committed to revolutionizing discovery by harnessing AI to enhance every aspect of the scientific method.

AbbVie is seeking a talented and motivated Associate Scientist II or Scientist I to join our dynamic In Vivo Pharmacology team in Cambridge. As part of our innovative research environment, you will play a crucial role in advancing our understanding of pharmacological mechanisms through in vivo studies. This position offers an exciting opportunity to contribute to groundbreaking research that has the potential to transform patient care.

As an Associate Scientist III, you will play a crucial role in advancing our scientific research initiatives. You will collaborate with cross-functional teams to design, execute, and analyze experiments that contribute to our innovative projects. Your expertise will help drive our mission forward, ensuring that we continue to push the boundaries of scientific discovery.

We are seeking a dedicated and detail-oriented Bench Scientist to join our innovative team at Artech Information Systems LLC. This entry-level role is perfect for recent graduates or individuals looking to kickstart their career in scientific research. The Bench Scientist will be responsible for conducting experiments, analyzing data, and contributing to various projects that advance our understanding of scientific principles.