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Location: San Francisco Mantle Squad US – Ecosystem Researcher San Francisco, US | Part-Time | 15–20 hours/week Role Overview Mantle is expanding its presence across the Americas and is seeking a high-signal ecosystem operator to help grow brand presence, community engagement, and offline traction. This part-time role (15–20 hours/week) is designed for individuals deeply embedded in either the crypto/X ecosystem or the San Francisco AI / builder community, with strong real-world credibility and the ability to convert offline interactions into meaningful ecosystem growth. The ideal candidate will act as a visible representative of Mantle in both digital and in-person environments: driving narrative, relationships, and ecosystem expansion across the US Responsibilities 1. Research, Trend Analysis & Narrative Development - Conduct in-depth research on Mantle, its ecosystem partners, and broader crypto, AI, and financial markets, with a focus on fast-moving narratives such as RWA prediction markets on-chain activity, and macro sentiment shifts - Identify emerging trends early and translate them into clear, actionable insights that inform narrative positioning, ecosystem opportunities, and strategic decision-making - Produce high-quality, narrative-driven research and analysis tailored for crypto-native audiences, institutional partners, and ecosystem communities (including blockchain clubs, universities, and research groups) - Break down complex trends such as RWA tokenization, prediction market signals, liquidity shifts, and macro cycles into clear, engaging, and distribution-ready content formats - Support internal strategy, campaigns, and ecosystem growth by surfacing trend-driven insights that shape positioning, timing, and focus 2. Ecosystem Representation & Offline Activation - Represent Mantle at industry events, conferences, meetups, and ecosystem gatherings across crypto, AI, and broader financial innovation spaces - Engage founders, builders, researchers, and institutional ecosystem participants in-person and convert interactions into meaningful relationships and opportunities - Support or co-host small-scale activations such as roundtables, research salons, and community events focused on emerging narratives (e.g. RWA, prediction markets, on-chain macro themes) - Act as a bridge between offline ecosystem conversations and Mantle’s internal teams by capturing real-time market and narrative signals from the field 3. Ecosystem Growth & Community Building - Leverage strong local and digital networks across crypto, AI, and developer ecosystems to expand Mantle’s presence in high-signal communities - Drive awareness and participation in Mantle’s ecosystem through narrative-led engagement across both online and offline channels - Support partnership development, introductions, and ecosystem expansion efforts tied to emerging sectors such as RWA, on-chain finance, and prediction markets Requirements - 2+ years of experience in crypto, Web3, or tech ecosystems (community, research, marketing, or growth roles) - Strong understanding of crypto culture and emerging narratives such as RWA, AI, …. - Ability to conduct lightweight research and translate insights into clear, well-written content or commentary for crypto-native audiences - Comfortable engaging in both online and offline ecosystem environments, including events, meetups, and community gatherings - Proven ability to build relationships with founders, builders, and ecosystem participants and follow up on meaningful connections - Strong communication skills with the ability to adapt messaging across different audiences (community, builders, partners) - Self-directed and reliable in executing responsibilities in a fast-paced, part-time, distributed environment Why Join Mantle Squad Americas - Be part of Mantle’s early expansion in North America - Work directly with global teams and ecosystem leaders - Gain access to high-impact crypto and AI events - Build your personal brand through research and storytelling - Grow into expanded regional or full-time ecosystem roles

Location: Paris; London Workplace: Hybrid TL;DR: We're looking for a research scientist to build autonomous, large-scale environments that push LLM agents (single and multi-agent) to failure, and study how they actually break. About us White Circle http://whitecircle.com is an AI Safety company building the safety, reliability, and optimization layer for AI systems. At the core of our platform are policies – simple natural-language rules that define what an AI model should and shouldn’t do. We automatically test, enforce, and continuously improve these policies at scale. - We’ve recently raised our Series A funding round, taking our total funding to $70M. Our investors include top funds, founders, and senior leaders at OpenAI, Anthropic, HuggingFace, Mistral, DeepMind, Datadog, Sentry, and others - We process over 100M+ API calls every month - We fine-tune and train our own LLMs so they run faster and cheaper than any open or proprietary model We’re a small, highly focused team. If you want to work deeply on hard problems, see your work ship to production quickly, and influence how AI safety is actually built – you’re the one we need. About the team White Circle's fundamental research team works on the science of how AI systems fail: where agents break, why misalignment and unsafe behaviours emerge, and how to catch them before they reach the real world. We build the evals, benchmarks, environments, and tooling that empirically study the most pressing AI safety concerns — some of which become the guardrails shipped in our products, and some of which become public writeups. What you’ll do - Build adversarial environments for agents: complex, uncertain settings that sit on the boundary of agent capability and alignment, where failure is informative rather than trivial. - Build realistic multi-agent environments and instrument them so emergent breakdowns are observable — failures that arise from the agents themselves, not ones scripted from the outside. - Run experiments end to end, against external APIs and our own models, orchestrating many agents in parallel. - Catalogue concrete agent failure modes and build the tooling to surface them at scale. - Turn findings into internal models of agent behaviour and into public writeups. You’ll fit right in if you - Have built at least one non-trivial agent environment or automated research pipeline that ran end to end (single- or multi-agent), and can talk through what broke and why. - Have strong software and AI engineering skills. Can independently orchestrate many agents and containers in parallel without that orchestration being the bottleneck. - Have a track record of empirical research in agents, red-teaming, or post-training where you defined the question, ran it, and drew a defensible conclusion. - Are a fast empirical iterator who is comfortable defining the question when there's no playbook: can take a fuzzy concern ("do these agents collude under pressure?") and turn it into a concrete, falsifiable experiment. - Are an AI power-user — fluent with frontier models and coding agents in your daily work. A big plus - Published research at A* venues on automated red-teaming, agentic environments, or post-training. - Experience building monitoring for model failures and anomalous behaviour. - Experience reproducing public benchmark results and finding where the original methodology is fragile or misleading. - An MSc or PhD in machine learning, computer science, cognitive science, computational neuroscience, physics, or a related quantitative field. - AI safety fellowship (MATS, ASTRA, Anthropic Fellows, etc.), or a comparable self-directed research record. Compensation & benefits - Competitive compensation, including equity - Flexible time off - Office in central London/Paris with flexible hybrid setup - Relocation support if you’re moving to Paris, available after your probationary period - Premium private health insurance - Mental health support, including coverage for therapy when you need it - Lunch and dinner covered when you work from the office - Learning and development support for courses, conferences, and opportunities to grow your skills - All the hardware, subscriptions, tools, and services you need - Team off-sites twice a year: we’ve recently been to the Alps, Saint-Tropez, and Marbella Process 1. Intro call with Talent 2. Test assignment 3. Technical interview with Head of Fundamental Research 4. Final interview with CEO

Location: Paris; London Workplace: Hybrid TL;DR: We're looking for a research engineer to build and maintain our internal suite of benchmarks, covering single/multi-turn content and agentic guardrails. The research engineer would also work with the team on projects studying agent behaviours in the wild. About us White Circle http://whitecircle.com is an AI Safety company building the safety, reliability, and optimization layer for AI systems. At the core of our platform are policies – simple natural-language rules that define what an AI model should and shouldn’t do. We automatically test, enforce, and continuously improve these policies at scale. - We’ve recently raised our Series A funding round, taking our total funding to $70M. Our investors include top funds, founders, and senior leaders at OpenAI, Anthropic, HuggingFace, Mistral, DeepMind, Datadog, Sentry, and others - We process over 100M+ API calls every month - We fine-tune and train our own LLMs so they run faster and cheaper than any open or proprietary model We’re a small, highly focused team. If you want to work deeply on hard problems, see your work ship to production quickly, and influence how AI safety is actually built – you’re the one we need. About the team White Circle's fundamental research team works on the science of how AI systems fail in the real world: where agents break, how misalignment actually looks like to the end user, and how it is present in the model internals. We build the evals, benchmarks, environments, and tooling that empirically study high-impact agent reliability concerns — some of which become the guardrails shipped in our products, and some of which become public writeups. What you’ll do Own and maintain our internal benchmark suite, covering single/multi-turn content guardrails and agentic safety. - Build benchmarks that distinguish specific model capabilities. - Work with the product team to build evals covering core functionality of our flagship models. - Build benchmarks for new features coming out of the research team. - Adapt and extend evals to new verticals and changing product data. - Work on research projects that study and quantify realistic agentic and LLM failure modes in the wild. You’ll fit right in if you - Have built an LLM benchmark from scratch that distinguished specific model capabilities (i.e., produced a measurable, defensible capability difference, not just a score). - Have built synthetic data for post-training textual or multimodal models. - Can reproduce a published benchmark result and identify where the original methodology is fragile or misleading. - You write Python that other people can build on. Our whole stack is Python; we want someone who has shipped and maintained production code and who factors messy problems into clean abstractions others can extend. - You can write efficient LLM inference setups, including sensible orchestration of parallel calls, retries, rate-limit handling. - An AI power-user — fluent with frontier models and coding agents day to day. A big plus - Automated red-teaming experience - Have worked across a range of agentic scaffolds and reproduced public benchmark results on them - Strong knowledge of existing reward-model / monitoring / safety benchmarks - One or more published papers in the evals / safety-evaluation space Compensation & benefits - Competitive compensation, including equity - Flexible time off - Office in central London/Paris with flexible hybrid setup - Relocation support if you’re moving to Paris, available after your probationary period - Premium private health insurance - Mental health support, including coverage for therapy when you need it - Lunch and dinner covered when you work from the office - Learning and development support for courses, conferences, and opportunities to grow your skills - All the hardware, subscriptions, tools, and services you need - Team off-sites twice a year: we’ve recently been to the Alps, Saint-Tropez, and Marbella Process 1. Intro call with Talent 2. Test assignment 3. Technical interview with Head of Fundamental Research 4. Final interview with CEO

Location: London and Hong Kong Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. Join QRT Academy as an Academic Partnerships & Research Lead in London or Hong Kong, working at the interface between academia and industry. QRT Academy connects leading research communities and talent with QRT through academic collaborations and research engagement initiatives. In this role, you will lead the development of QRT’s academic collaborations, working directly with leading institutions and research groups globally to shape and contribute to research projects and collaboration opportunities. Your future role at QRT: Lead the design and delivery of engagement programmes with academic partner institutions, including research collaborations, visiting practitioner initiatives, and student programmes Collaborate directly with academic partners on research projects, including contributing to research direction, publications, and conference engagement Build and develop long-term partnerships with leading academics, departments, and research groups across priority institutions Act as a primary point of contact for partner institutions, collaborating closely with academics and researchers to shape collaboration opportunities Identify and engage high-potential students and early-career researchers through academic programmes and networks Develop and scale the model for academic partnerships across institutions and regions Ensure alignment between academic engagement activities and broader research and talent objectives Work closely with internal teams to connect academic collaborations with QRT’s research priorities Partner with the operations function to support effective delivery of programmes, maintaining focus on academic content and relationships Your present skillset: PhD in a quantitative discipline (mathematics, statistics, computer science, engineering or related field) with a strong research background Experience managing or contributing to academic collaborations, research programmes, or university partnerships Strong stakeholder management skills, with the ability to engage effectively with senior academics and researchers Strong understanding of how leading research institutions structure external collaborations Ability to shape and manage complex academic partnerships across institutions and regions Strong organisational and problem-solving skills, with the ability to operate in evolving or ambiguous environments Experience working in globally distributed or research-intensive environments is advantageous Strong engagement with research and the academic ecosystem QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Location: Chicago, New York Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. Your future role within QRT: We are seeking a Market Microstructure Researcher to help optimize exchange connectivity and interaction for our high-frequency trading strategies. You will analyse network and exchange protocols, automate performance metrics, and lead experiments to improve our trading operations, with a focus on latency-sensitive exchanges. Network & Protocol Analysis: Analyse network and exchange protocol captures to identify inefficiencies and improve communication performance Exchange Research & Liaison: Research exchange features, attend presentations, and communicate with exchange counterparts to gather insights Execution Optimization: Reverse-engineer trading systems and design and conduct experiments to improve fill rates Cross-team Communication: Collaborate directly with trading and research teams to ensure best application of findings and direct PnL impact Data Analysis: Effectively work with large and robust datasets to identify and resolve inefficiencies in internal execution systems and exchange communication Your present skillset: Degree in Computer Science, Engineering, or a related field 5+ years of experience in data analysis and/or low-level systems and network engineering Strong skills in Python and time-series analysis Understanding of network protocols such as TCP/IP and Ethernet Familiarity with market microstructure and low-latency trading is a plus Advanced networking and GNU/Linux knowledge is a plus Base salary range for this position is $180,000 to $260,000 per year. QRT Total Compensation includes discretionary performance-based bonuses and a competitive benefits package.

Location: Hong Kong Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset, which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. As part of our Research Platforms team, you will design and build the distributed systems that enable large-scale computational workloads to run efficiently, securely, and reliably across our global research infrastructure. This role sits at the intersection of distributed systems, platform engineering, and high-performance computing. You will work on the foundational services researchers depend on every day, including workload orchestration, scheduling, security, observability, and platform tooling. What You'll Do Design, build, and operate distributed services that manage compute workloads and data access across large-scale infrastructure Develop platform APIs and tooling that improve the productivity of quantitative researchers Improve the reliability, scalability, and performance of compute-intensive research workflows Build solutions for scheduling, resource management, observability, and security Partner closely with researchers and infrastructure teams to translate complex requirements into scalable platform capabilities Take ownership of systems end-to-end, from design and implementation through production operation What We're Looking For Required BS, MS, or PhD in Computer Science or a related field, or equivalent practical experience 5+ years of experience building and operating large-scale distributed systems in production Strong proficiency in C++, Java, Rust, Go, or similar systems languages Strong understanding of distributed systems, concurrency, performance, reliability, and fault tolerance Experience designing services, platforms, or infrastructure used by other engineers Preferred Experience with internal developer platforms, cloud infrastructure, orchestration systems, or HPC environments Familiarity with GPU-accelerated workloads and modern ML frameworks such as PyTorch or TensorFlow Experience supporting researchers, data scientists, or other highly technical users Exposure to quantitative finance or large-scale data-intensive environments Why Join QRT? Solve challenging distributed systems and infrastructure problems at scale Build platforms that directly accelerate research and innovation Work closely with world-class quantitative researchers and engineers Take ownership of critical systems in an environment that values technical excellence, autonomy, and impact QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Location: Amsterdam Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. Your future role within QRT: We are seeking a Market Microstructure Researcher to help optimize exchange connectivity and interaction for our high-frequency trading strategies. You will analyse network and exchange protocols, automate performance metrics, and lead experiments to improve our trading operations, with a focus on latency-sensitive exchanges. Network & Protocol Analysis: Analyse network and exchange protocol captures to identify inefficiencies and improve communication performance Exchange Research & Liaison: Research exchange features, attend presentations, and communicate with exchange counterparts to gather insights Execution Optimization: Reverse-engineer trading systems and design and conduct experiments to improve fill rates Cross-team Communication: Collaborate directly with trading and research teams to ensure best application of findings and direct PnL impact Data Analysis: Effectively work with large and robust datasets to identify and resolve inefficiencies in internal execution systems and exchange communication Your present skillset: Degree in Computer Science, Engineering, or a related field 5+ years of experience in data analysis and/or low-level systems and network engineering Strong skills in Python and time-series analysis Understanding of network protocols such as TCP/IP and Ethernet Familiarity with market microstructure and low-latency trading is a plus Advanced networking and GNU/Linux knowledge is a plus QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Location: London, Paris, Zurich Eligible candidates : Final-year PhD students or postdoctoral researchers Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. Over the years, QRT has invested in a global research and execution platform which has been deployed to cover all geographies and asset classes. This platform covers a broad spectrum from high to low frequency trading systems. Our culture is centred around technology, automation, and industrialized processes. We operate in multiple languages from C++ to Python and embrace open-source software. Your future role within QRT You will join a team of quantitative researchers to learn how to design trading algorithms in a real-world data environment – a fast track to become a seasoned quantitative researcher. Surrounded by peers who have successfully transitioned from academia to applied research, you will receive mentorship from experienced professionals who will help you translate your theoretical expertise into real-world impact. The research environment at QRT is designed to be collaborative and intellectually stimulating. Within one of QRT's systematic teams - spanning high, mid, and low-frequencies - your core objective will be to develop high-quality predictive signals: Leverage access to vast and diverse datasets to identify hidden statistical patterns and market opportunities. Collaborate with fellow researchers to exchange ideas and refine methodologies. Translate theoretical models into production-ready signals. Lead the full research cycle - from idea generation to implementation. Your present skillset Holding or pursuing a PhD (final year) degree in a quantitative field such as statistics, mathematics, physics, biology, computer science, or engineering. A pragmatic attitude towards translating theoretical models into real-world data problems. Proficiency in Python (preferred) or another leading programming language such as R, MATLAB, C++, or C#. Experience working with large datasets across multiple time frames (a plus). Ability to multitask in a fast-paced environment with attention to detail. Intellectual curiosity to explore new data, solve complex problems, and connect ideas across disciplines. Ability to work autonomously, in a collegial and collaborative setting, and with colleagues from diverse backgrounds and areas of expertise. Strong communication skills. Fluency in English (additional languages are a plus). Interviewing: Apply online: All applications are reviewed by our Talent Acquisition Team, on a rolling basis. Interviews: Conducted on-site or via Teams, they assess both your technical expertise and alignment with our collaborative culture. We invite candidates for the Quantitative Research position to take part in one of our Data Challenges. This task is designed to give you insight into the daily responsibilities of the role and allows us to assess your abilities and interest: Challenge data (ens.fr) QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance

Location: Anywhere Anagram is a digital assets holding company where we build and incubate new crypto projects. MISSION Build and accelerate decentralized technology to reorder our economies into communities of distributed and individual ownership VALUES At Anagram we play, build, and win as a team. We like to have fun while we relentlessly pursue excellence in everything we do. We are entrepreneurs first, thinking radically outside the box, creatively and futuristically. We are working hard to re-order the world while focusing on sincere open-mindedness, curiosity and radical transparency. THESIS More and more people will continue to enter the digital asset ecosystem. All existing assets will be digitized and new assets will be created. Digitized assets will become financialized and interoperable. Web3 will enable open access to all modern and future forms of finance. Anyone, anywhere, will be able to create financial products. Through active participation, Anagram is committed to accelerating the digital financialization of everything and enabling everyone to participate in the digital asset ecosystem. Looking forward to working together! If this isn't the right fit, we are hiring across a number of roles and would be happy to consider your candidacy. Feel free to email your resume to recruiting@anagram.xyz

Location: London Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. Your future role within QRT: Create high quality Crypto signals on various exchanges and platforms. Monitor your own trading, strategy performance and all relevant risks. Your core objective is to create high quality predictive signals. By leveraging access to large and diversified datasets you will identify statistical patterns and opportunities. Share and discuss research results, methodology, data sets and processes with other researchers. Implement the signals and the relevant datasets within the global execution platform. Monitor signal behaviour and model performance over time within your strategies. You would lead the full strategy research cycle from signal generation to implementation. Your present skillset: Proven track record in delivering successful Crypto systematic strategies. Minimum 2 years of experience in the financial industry. Advanced degree in a quantitative field such as data science, statistics, mathematics, physics or engineering. Strong knowledge in statistics, machine learning, NLP or AI techniques is a plus. Capacity to multi-task in a fast-paced environment while keeping strong attention to detail. Good fundamental crypto knowledge is a plus. Experience with one or more of the below is a plus: Crypto specific data sets, DeFi, latency-sensitive, ML/AI or strategies in production Coding skills required in at least one leading programming language, Python preferred, C++ is beneficial. Intellectual curiosity to explore new data sets, solve complex problems, drive innovative processes and connect the dots between multiple fields. Capacity to work with autonomy within a collegial and collaborative environment. Strong capacity to communicate with technologists, data scientists and traders across the globe. QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees to achieve a healthy work-life balance.

Location: Paris Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. Your future role within QRT Your core objective is to create high quality predictive signals. By leveraging access to large and diversified datasets you will identify statistical patterns and opportunities. Share and discuss research results, methodology, data sets and processes with other researchers. Implement the signals and the relevant datasets within the global execution platform. Monitor signal behaviour and model performance over time. You would lead the full strategy research cycle from signal generation to implementation. Your present skillset Advanced degree in a quantitative field such as data science, statistics, mathematics, physics or engineering. Strong knowledge in statistics, machine learning, NLP or AI techniques is a plus. Capacity to multi-task in a fast paced environment while keeping strong attention to detail. Coding skills required in at least one leading programming language (Python, R, Matlab and /or C++, C#). Experience in exploring large datasets across multiple time frames is a plus. Intellectual curiosity to explore new data sets, solve complex problems, drive innovative processes and connect the dots between multiple fields. Capacity to work with autonomy within a collegial and collaborative environment. Strong capacity to communicate with technologists, data scientists and traders across the globe. Proven track record in delivering successful systematic strategies. QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Location: Zurich Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. Your future role within QRT Your core objective is to create high quality predictive signals. By leveraging access to large and diversified datasets you will identify statistical patterns and opportunities. Share and discuss research results, methodology, data sets and processes with other researchers. Implement the signals and the relevant datasets within the global execution platform. Monitor signal behaviour and model performance over time. You would lead the full strategy research cycle from signal generation to implementation. Your present skillset Advanced degree in a quantitative field such as data science, statistics, mathematics, physics or engineering. Strong knowledge in statistics, machine learning, NLP or AI techniques is a plus. Capacity to multi-task in a fast paced environment while keeping strong attention to detail. Coding skills required in at least one leading programing language (Python, R, Matlab and /or C++, C#). Experience in exploring large datasets across multiple time frames is a plus. Intellectual curiosity to explore new data sets, solve complex problems, drive innovative processes and connect the dots between multiple fields. Capacity to work with autonomy within a collegial and collaborative environment. Strong capacity to communicate with technologists, data scientists and traders across the globe. Proven track record in delivering successful systematic strategies. QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Location: Dubai Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. Your future role within QRT Your core objective is to create high quality predictive signals. By leveraging access to large and diversified datasets you will identify statistical patterns and opportunities. Share and discuss research results, methodology, data sets and processes with other researchers. Implement the signals and the relevant datasets within the global execution platform. Monitor signal behaviour and model performance over time. You would lead the full strategy research cycle from signal generation to implementation. Your present skillset Advanced degree in a quantitative field such as data science, statistics, mathematics, physics or engineering. Strong knowledge in statistics, machine learning, NLP or AI techniques is a plus. Capacity to multi-task in a fast paced environment while keeping strong attention to detail. Coding skills required in at least one leading programing language (Python, R, Matlab and /or C++, C#). Experience in exploring large datasets across multiple time frames is a plus. Intellectual curiosity to explore new data sets, solve complex problems, drive innovative processes and connect the dots between multiple fields. Capacity to work with autonomy within a collegial and collaborative environment. Strong capacity to communicate with technologists, data scientists and traders across the globe. Proven track record in delivering successful systematic strategies. QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Location: London Your future role within QRT Your core objective is to create high quality predictive signals. By leveraging access to large and diversified datasets you will identify statistical patterns and opportunities. Share and discuss research results, methodology, data sets and processes with other researchers. Implement the signals and the relevant datasets within the global execution platform. Monitor signal behaviour and model performance over time. You would lead the full strategy research cycle from signal generation to implementation. Your present skillset Advanced degree in a quantitative field such as data science, statistics, mathematics, physics or engineering. Strong knowledge in statistics, machine learning, NLP or AI techniques is a plus. Capacity to multi-task in a fast paced environment while keeping strong attention to detail. Coding skills required in at least one leading programming language (Python, R, Matlab and /or C++, C#). Experience in exploring large datasets across multiple time frames is a plus. Intellectual curiosity to explore new data sets, solve complex problems, drive innovative processes and connect the dots between multiple fields. Capacity to work with autonomy within a collegial and collaborative environment. Strong capacity to communicate with technologists, data scientists and traders across the globe. Proven track record in delivering successful systematic strategies.

Location: Mumbai Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high-quality returns for our investors. Your future role within QRT Your core objective is to create high-quality predictive signals. By leveraging access to large and diversified datasets you will identify statistical patterns and opportunities. Share and discuss research results, methodology, data sets and processes with other researchers. Implement the signals and the relevant datasets within the global execution platform. Monitor signal behaviour and model performance over time. You would lead the full strategy research cycle from signal generation to implementation. Your present skillset Advanced degree in a quantitative field such as data science, statistics, mathematics, physics or engineering. Strong knowledge in statistics, machine learning, NLP or AI techniques is a plus. Capacity to multi-task in a fast paced environment while keeping strong attention to detail. Coding skills required in at least one leading programing language (Python, R, Matlab and /or C++, C#). Experience in exploring large datasets across multiple time frames is a plus. Intellectual curiosity to explore new data sets, solve complex problems, drive innovative processes and connect the dots between multiple fields. Capacity to work with autonomy within a collegial and collaborative environment. Strong capacity to communicate with technologists, data scientists and traders across the globe. Proven track record in delivering successful systematic strategies. QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees to achieve a healthy work-life balance.

Isomorphic Labs is looking for a Research Investigator to design and run biochemical biophysical and cellular assays for novel therapeutic modalities and generate ML-ready data that improves AI drug design models.

Isomorphic Labs is looking for a Research Leader in in vitro pharmacology to build and lead a team of biologists and own experimental pharmacology strategy and screening cascades for novel therapeutic modalities.

The AI Security Institute is looking for a Research Scientist to lead and contribute to research on how frontier AI systems influence people.