Synthetic Sciences jobs

Applied Sciences Manager , Ads Brand Safety and Suitability London, England, GBR Amazon Ads Brand Safety & Suitability protects advertisers from exposure to unsafe, unsuitable, or policy-violating content across web, mobile app, CTV, and audio advertising inventory. Our mission is to ensure that every ad impression delivered through Amazon's demand-side platform appears adjacent to content that meets advertiser trust expectations while giving brands granular controls to define suitability on their own terms. We operate at the intersection of advertiser trust, publisher quality, and supply integrity. AI is fundamentally changing the content landscape. Content is now generated at unprecedented scale - faster, cheaper, and increasingly sophisticated. Low-quality, deceptive, AI-generated, and synthetic content evolves in real time, constantly adapting to evade detection. The volume and velocity of new content entering the advertising system has outpaced traditional classification approaches. We are looking for an Applied Science Manager to lead the next generation of AI-powered Brand Safety and Content Classification systems designed to protect advertisers and elevate supply quality at internet scale. This is not a traditional classification problem. Your team will build systems that make millisecond-level decisions across billions of content signals while continuously adapting to emerging content risks driven by generative AI. You will own the science roadmap for LLM-powered classification and semantic understanding, real-time multimodal content evaluation, adversarial ML and adaptive model resilience, proactive risk intelligence and content risk hunting, AI-generated and synthetic content detection, and large-scale abusive content system identification and disruption. You will define how modern AI separates high-quality

Advisor — Synthetic Chemist / Peptide Therapeutics (Indianapolis) US, Indianapolis IN posted: Posted 21 Days Ago

CMC Leader Synthetics - Portfolio Management Beerse, Antwerp, Belgium posted: Posted 10 Days Ago

Doctoral Thesis - Automated Layout Synthesis for Scalable Quantum Computing Cryogenic Circuit Design Automation (f/m/div) Munich (Germany)

Director Engineering - Synthetic Molecule Design and Development US, Indianapolis IN posted: Posted 30+ Days Ago

HPE Labs - Postdoctoral Research Scientist: Generative AI for Photonic and Analog Electronic Design Automation Diegem, Flemish Brabant, Belgium Exciting opportunity for a Postdoctoral Research Scientist to drive innovation in generative AI for photonic and analog electronic design automation. Collaborate with multidisciplinary experts, develop cutting-edge AI-assisted methodologies, and contribute to impactful research in a dynamic, hybrid work environment. Shape the future of next-generation optical and electronic systems with HPE Labs.

Senior Production Support Analyst, Synthetic Prime Singapore, Singapore posted: Posted 3 Days Ago

Member of the Technical Staff, Cheminformatics New York HQ 🗽 | Remote The Role Output has built a biological reasoning model that understands biology at the scale and complexity life actually operates. Our model independently learned the principles of molecular interactions, opening up drug treatments that were previously impossible. We're already generating therapies that traditional approaches cannot reach. The hardest problems in both AI and biology are being solved here, and there is room for you to own one. Output is currently in stealth, operated by a team of repeat founders and biotech veterans with multiple exits in AI x Bio, and backed by top-tier VCs including Y Combinator. You accelerate the path from a generated molecule to a synthesized compound. This role continues to build the models and computational methods that optimize Output's molecular generation for practical chemistry. - You will continue developing and training models that incorporate knowledge of chemical synthesis routes and reactions, steering molecular generation toward molecules that are efficient to synthesize - You will build scalable computational tools and methods that evaluate synthetic feasibility across generated molecular libraries, systematically and at scale - You will interpret model inputs and outputs in chemistry terms, translating between the language of generative AI and the language of synthesis - You will work with the drug discovery and model teams, bringing chemistry expertise to molecular evaluation and candidate prioritization - You will build and maintain cheminformatics pipelines for molecular analysis, property calculation, and candidate assessment About You You have

Senior Manager, Synthetics Product Quality Integrator (PQI) 5 Locations posted: Posted 3 Days Ago

RNA synthetic automation specialist China, Shang Hai-上海 posted: Posted 30+ Days Ago

Member of the Technical Staff, Molecular Generation New York HQ 🗽 Output has built a biological reasoning model that understands biology at the scale and complexity life actually operates. Our model independently learned the principles of molecular interactions, opening up drug treatments that were previously impossible. We're already generating therapies that traditional approaches cannot reach. The hardest problems in both AI and biology are being solved here, and there is room for you to own one. Output is currently in stealth, operated by a team of repeat founders and biotech veterans with multiple exits in AI x Bio, and backed by top-tier VCs including Y Combinator. You will lead the design and development of Output's generative models, working across molecular modalities to build systems that produce novel, biologically grounded molecules. This role spans the full arc from research to trained model: you design architectures, develop training approaches, run experiments on distributed GPU clusters, and evaluate results. - You will design and build generative architectures for molecular data spanning multiple modalities, including small molecules, peptides, mini proteins and more - You will develop training approaches that learn from diverse biological signal, ensuring the model composes genuinely novel structures - You will build methods for controllable, targeted generation, enabling the model to produce molecules with specified biological properties while satisfying real-world chemical constraints - You will integrate biological reasoning from our foundation model into the generative pipeline, using learned biological representations to guide and condition generation - You will own training end-to-end:

Principal Scientist — Synthetic Chemist / Peptide Therapeutics (Indianapolis) US, Indianapolis IN posted: Posted 30+ Days Ago

Postdoctoral Scholar — AI Researcher for Critical Mineral Discovery Remote Position: Fully funded 3-year postdoctoral fellowship at Stanford Mineral-X, advised by Prof. Jef Caers, in collaboration with KoBold Metals, developing and deploying new methods for critical mineral exploration and resource definition. The scholar will develop and apply AI, muon tomography, seismic imaging, and geophysical inversion methods to discover and characterize copper, nickel, lithium, cobalt, and rare earth deposits using real exploration data from active field programs. More information here: https://postdocs.stanford.edu/postdoc-admins/policy/funding-rates-and-guidelines. Research Scope - Multi-physics inversion: Develop stochastic and ensemble inversion frameworks that jointly assimilate muon flux, seismic (active-source, passive, DAS), magnetics, gravity, and EM data into 3D subsurface property models with calibrated uncertainty. - Muon tomography: Forward modeling, sensor placement optimization, and inversion of cosmic-ray muon attenuation data from borehole and surface detectors to constrain ore body density at depth. - Machine learning for geoscience: Apply deep generative models, geostatistical priors, and physics-informed neural networks to regional-to-deposit-scale targeting and resource estimation. Build pipelines that respect geological process constraints rather than purely data-driven correlations. - Decision under uncertainty: Extend Mineral-X's intelligent agent framework to sequential data acquisition decisions (drill hole placement, geophysical survey design) that maximize information value per dollar. Required Qualifications - PhD (fully completed, and within 4 years of graduation) in physics, applied physics, geophysics, computational earth sciences, machine learning, applied mathematics, or related field. - Strong Python proficiency (NumPy, PyTorch or JAX, scientific stack); experience with HPC, GPU computing, and reproducible research workflows. - Track record of publishing

Research Scientist Intern, Monetization Generative AI - LLM (PhD) Bellevue, WA; Menlo Park, CA; Seattle, WA Meta was built to help people connect and share, and over the last decade our tools have played a critical part in changing how people around the world communicate with one another. With over a billion people using the service and more than fifty offices around the globe, a career at Meta offers countless ways to make an impact in a fast growing organization. We are committed to advancing the field of artificial intelligence by making fundamental advances in technologies to help interact with and understand our world. We are seeking individuals passionate in areas such as deep learning, computer vision, audio and speech processing, natural language processing, machine learning, reinforcement learning, computational statistics, and applied mathematics. Our interns have an opportunity to make core algorithmic advances and apply their ideas at an unprecedented scale. Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year. Responsibilities: - Perform research to advance the science and technology of intelligent machines - Develop novel and accurate NLP algorithms and systems, leveraging Deep Learning and Machine Learning on big data resources - Analyze and improve efficiency, scalability, and stability of various deployed systems - Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results - Publish research results and contribute to research that can be applied to Meta product development Minimum qualifications: - Currently has or

Sr. Advisor/Director – Synthetic Peptide Process development Scientist India, Hyderabad posted: Posted 30+ Days Ago

Laborant Formulierungsentwicklung SMTD (Synthetic Molecule Technical Development) (m/w/d) DE - Monheim posted: Posted 4 Days Ago

Forward Deployed Scientist Lausanne / Hybrid / Remote | Hybrid | Remote Adaptyv is building an automated lab thats let AI agents run biology experiments. We're entering the era of agentic science where AI models can now design novel proteins, propose hypotheses, and iterate on experimental results. But they can't run the experiments themselves - that's still a manual, months-long process. We're building the infrastructure that gives AI agents access to the physical world. We are one of the fastest growing biotech companies, trusted by leading biopharmas, frontier AI labs, and the techbio companies pushing the field forward. This is a rare chance to help advance some of the most important work happening in biotech today. Our automated lab is powered by a deep software + hardware stack: lab instruments worth millions of USD reverse-engineered into API-controllable hardware, dozens of devices orchestrated through complex workflows, full observability on everything that happens in the lab, processing pipelines for messy physical-world data, and AI systems that troubleshoot production results and accelerate assay development. We're growing rapidly and are hiring for talented people to scale and support the massive demand for AI-driven wet lab experimentation. ABOUT THE ROLE You're a scientist on staff who works shoulder-to-shoulder with customers to help them design better proteins and get more out of every experiment. You sit between their design models and our lab: helping them scope a campaign, pick the right design approach for the problem, make sense of the data that comes back, and decide

VP - Asia Synthetic Prime Brokerage Execution Trader Singapore, Singapore posted: Posted 16 Days Ago

Sr. Data Platform Engineer - Computer System Validator New York, New York; Salt Lake City, Utah Your work will change lives. Including your own. Recursion is a leading, clinical-stage TechBio company decoding biology to industrialize drug discovery. Central to its mission is the Recursion Operating System (OS), a platform built across diverse technologies that continuously expands one of the world's largest proprietary biological, chemical and patient-centric datasets. Recursion leverages sophisticated machine-learning algorithms to distill from its dataset a collection of trillions of searchable relationships across biology and chemistry unconstrained by human bias. By commanding massive experimental scale-up to millions of wet lab experiments weekly-and massive computational scale-owning and operating one of the most powerful supercomputers in the world-Recursion is uniting technology, biology, chemistry and patient-centric data to advance the future of medicine. In this role, you will: Build, scale, and operate in a validated data platform . You will be a member of the platform team responsible for building, operating, and tuning a data platform with petabyte scale data, and maintaining a GxP-compliant data platform for clinical data. These platforms allow our users to discover and query across the breadth of our data at Recursion, which includes a chemistry library of billions of compounds, cellular microscopy images taken in millions of different experimental contexts, and millions of assay results, all supporting Recursion's drug discovery. Engineer Data Integrity and Traceability: You will ensure data flows with integrity in the validated environment by building the automated audit trails and lineage required by

Synthetic Chemist High Potency Lab - Lilly Medicine Foundry 2 Locations posted: Posted 11 Days Ago

Research Scientist / Engineer - Efficient Modeling Mountain View, Mountain View,, California, United States At Rhoda AI, we're building the next generation of generalist intelligent robots. We own the full robotics stack from high-performance hardware and robot systems to the infrastructure and state-of-the-art foundation world models that control our robots. Our robots are designed to be generalists capable of operating in complex, real-world environments and handling long-tail edge cases, made possible by our cutting edge research and end-to-end system design. We've raised over $400M and are investing aggressively in model research, infrastructure, hardware development, and manufacturing scale-up to make generalist robotics a reality. We're looking for a Research Scientist or Research Engineer focused on model efficiency - making our foundation world models faster, smaller, and more deployable without sacrificing capability. This work is critical to closing the gap between research-scale models and real-time operation on robot hardware. What You'll Do - Research and implement model compression techniques: quantization, pruning, structured sparsity, distillation, and low-rank approximation - Design efficient architectures and attention mechanisms suited to real-time inference on edge and robot hardware - Develop training strategies that produce better accuracy-efficiency tradeoffs from the start - Profile and benchmark models across hardware targets to identify and resolve efficiency bottlenecks - Build evaluation frameworks that measure capability retention after compression or architecture changes - Collaborate with training systems and deployment teams to ensure efficient models translate to faster real-world inference - Publish and present work at top-tier venues What We're Looking For -

Analyst - Synthetic Prime, Client Services New York, New York posted: Posted 7 Days Ago

Associate - Synthetic Prime, Client Services New York, New York posted: Posted 7 Days Ago

Research Scientist (Generative Modeling) San Francisco About World Labs: We build foundational world models that can perceive, generate, reason, and interact with the 3D world - unlocking AI's full potential through spatial intelligence by transforming seeing into doing, perceiving into reasoning, and imagining into creating. We believe spatial intelligence will unlock new forms of storytelling, creativity, design, simulation, and immersive experiences across both virtual and physical worlds. We bring together a world-class team, united by a shared curiosity, passion, and deep backgrounds in technology - from AI research to systems engineering to product design - creating a tight feedback loop between our cutting-edge research and products that empower our users. Role Overview We are looking for a talented Research Scientist with a strong background in generative modeling, particularly diffusion models, to join our modeling team. This role is ideal for candidates with deep expertise in diffusion models applied to images, videos, or 3D assets and scenes. While not required , experience in one or more of the following areas is a strong plus : - Large-scale model training - Data curation for pretraining or post-training - Tokenizers and VAEs for image, video, or 3D data - Long-context architectures - 3D vision You will collaborate closely with researchers, engineers, and product teams to bring advanced 3D modeling and machine learning techniques into real-world applications, ensuring that our technology remains at the forefront of visual innovation. This role involves significant hands-on research and engineering work, driving projects from conceptualization through to production