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Dynamical Systems Research Jobs (NOW HIRING)

... Dynamical Systems, Aerospace Engineering, Statistics and Probability, or a related field. * A ... A Research Scientist should have effective written and verbal communication skills, with the ...

Senior Research Scientist

Broomfield, CO · On-site

$99K - $126K/yr

... Dynamical Systems, Aerospace Engineering, Statistics and Probability, or a related field. * A ... A Research Scientist should have effective written and verbal communication skills, with the ...

An MS/PhD or equivalent research/project experience is strongly preferred. ‱ A '0-to-1' mindset ... dynamical systems (ODEs, PDEs, SDEs), ideally with experience analyzing the stability, noise ...

... Dynamical Systems, Aerospace Engineering, Statistics and Probability, or a related field. * A ... A Research Scientist should have effective written and verbal communication skills, with the ...

We are particularly interested in candidates whose research integrates AI/ML with strong foundations in areas such as control, optimization, dynamical systems, decision-making,designor related ...

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Dynamical Systems Research information

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How much do dynamical systems research jobs pay per year?

As of Sep 14, 2026, the average yearly pay for dynamical systems research in the United States is $68,438.00, according to ZipRecruiter salary data. Most workers in this role earn between $43,500.00 and $85,000.00 per year, depending on experience, location, and employer.

What is dynamical systems research?

Dynamical Systems Research is the scientific study of systems that evolve over time according to specific rules, often described by mathematical equations. Researchers in this field investigate how systems change, predict long-term behavior, and analyze stability and patterns, such as chaos or periodicity. Applications range from physics and biology to economics and engineering, helping to understand everything from weather patterns to population dynamics. This interdisciplinary field often uses tools from mathematics, computer science, and data analysis.

What are the key skills and qualifications needed to thrive in dynamical systems research?

To excel in Dynamical Systems Research, a strong background in mathematics, particularly differential equations and nonlinear systems, along with an advanced degree (often a PhD) is essential. Familiarity with computational tools such as MATLAB, Python, or Mathematica, and experience using simulation or modeling software, are typically required. Analytical thinking, problem-solving abilities, and clear scientific communication are crucial soft skills for success in this field. These skills are vital for advancing theoretical understanding, conducting rigorous research, and effectively sharing findings with both academic and applied audiences.

What are some common challenges faced by researchers in the field of dynamical systems, and how can they be addressed?

Researchers in dynamical systems often encounter challenges such as modeling complex, nonlinear phenomena, managing large datasets, and staying updated with rapidly evolving computational methods. Collaboration with interdisciplinary teams and regular engagement with conferences or workshops can help address these challenges. Utilizing advanced simulation tools and seeking mentorship from experienced researchers are also effective strategies for overcoming technical and conceptual obstacles.

What is the difference between Dynamical Systems Research vs Data Scientist?

AspectDynamical Systems ResearchData Scientist
Required CredentialsAdvanced degrees in mathematics, physics, or engineeringDegree in computer science, statistics, or related fields
Work EnvironmentResearch labs, academia, or R&D departmentsTech companies, finance, healthcare, or consulting firms
Industry UsageModeling complex systems, chaos theory, nonlinear dynamicsData analysis, predictive modeling, machine learning

While both roles involve analytical skills and quantitative methods, Dynamical Systems Research focuses on understanding complex systems through mathematical modeling, whereas Data Scientists analyze data to extract insights and build predictive models. The roles often overlap in research settings but differ in application and industry focus.

What are popular job titles related to Dynamical Systems Research jobs?

For Dynamical Systems Research jobs, the most frequently searched job titles are:

Infographic showing various Dynamical Systems Research job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 85% Full Time, 10% Part Time, and 3% Contract. Highlights an 85% Physical, 2% Hybrid, and 13% Remote job distribution, with an average salary of $68,438 per year, or $32.9 per hour.

Research Scientist, Frontier Health, DeepMind

Mountain View, CA ‱ On-site

Google Inc.
Software Development ‱ 10K+ employees

Other

Posted 16 days ago


Key responsibilities

  • Conduct fundamental and applied machine learning research to develop physiological and behavioral world models simulating human biology.

  • Design novel machine learning architectures for multi-modal clinical telemetry and longitudinal EHRs.

  • Build and maintain evaluation benchmarks to assess disease trajectory predictions, clinical events, and treatment simulations.


Google rating

8.8

Company rating: 8.8 out of 10

Based on 103 frontline employees who took The Breakroom Quiz


Job description

Share Research Scientist, Frontier Health, DeepMind

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DeepMind Mountain View, CA, USA

Share Research Scientist, Frontier Health, DeepMind

  • PhD in Computer Science, Machine Learning, Computational Biology, Applied Mathematics, Physics, or equivalent practical experience.
  • 2 years of experience (industry or internships) in building world models for adaptive systems, foundation models, continuous dynamical systems, state-space models, and deep generative architectures.
  • Experience with model robustness, out-of-distribution generalization, and uncertainty quantification.
  • Research experience with first-author publications at machine learning venues or domain journals (NeurIPS, ICML, ICLR, etc.).
Preferred qualifications:
  • Strong experience learning underlying system dynamics from partially observable environments, managing irregular sampling, missing modalities, and latent state estimation.
  • Experience applying these methodologies to biomedical domains, framing multi-modal healthcare data, longitudinal EHRs (e.g., MIMIC-IV), and physiological telemetry as complex adaptive systems.
  • Proficiency in Python and modern deep learning frameworks (JAX, PyTorch, or TensorFlow).
  • Strong collaborative skills for working in interdisciplinary teams alongside clinical partners.

Passion for AI technology and all of its possibilities.

About the job

As an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.

As a Research Scientist, you'll also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.

Frontier Health is developing foundational biomedical intelligence to transform outcomes for complex systemic diseases. We build physiological world models and agentic decision systems that simulate disease advancement and treatment responses across critical care, oncology, and metabolic health. By bridging multi-modal telemetry, EHR data, and reinforcement learning, we are shifting healthcare from reactive observation to proactive intervention.

As a Research Scientist, you will advance foundational models for human biology. You will manage problems spanning continuous dynamical systems and counterfactual reasoning to decode pathophysiology.

Artificial intelligence will be one of humanity’s most transformative inventions. At DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.

We are pushing the boundaries across multiple domains. Our global teams offer learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

  • Conduct fundamental and applied ML research to develop physiological and behavioral world models simulating continuous-time human biology.
  • Design novel machine learning architectures (e.g., state-space models, neural dynamical systems) for multi-modal clinical telemetry and longitudinal EHRs (e.g., MIMIC-IV).
  • Build and maintain robust evaluation benchmarks (OxyBench) to assess disease trajectory predictions, acute clinical events (e.g., sepsis), and counterfactual treatment simulations.
  • Collaborate cross-functionally with ML researchers, software engineers, and external clinical partners across Mountain View, London, and Paris.
  • Publish original research in top machine learning conferences and leading medical journals.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

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