AI Research Scientist (ML for Physical Systems)

Remote

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

YesVisa

Industrial Automation, Artificial Intelligence, AI & Machine Learning, Software DevelopmentIndustries

Requirements

Candidates should possess a PhD in a relevant field such as machine learning, computer science, physics, or a related discipline, with a strong foundation in physical systems including thermodynamics, fluid mechanics, and control systems. Experience in reinforcement learning and a proven track record of applying AI to complex problems are essential. The ideal candidate will have expertise in interdisciplinary fields and be located in the UK, USA (California, Colorado, Connecticut, Georgia, Florida, Indiana, Maryland, Minnesota, Missouri, Nebraska, New York, North Carolina, Pennsylvania, South Carolina, Tennessee, Texas, Virginia, Washington), or Canada (Ontario, British Columbia, Alberta).

Responsibilities

Research Scientists will lead the development of novel algorithmic architectures for intelligent control systems in the industrial sector. They will collaborate with other AI researchers on applied real-world problems, demonstrating algorithmic feasibility and enhancing capabilities. Responsibilities include designing and implementing prediction and control algorithms for complex, nonlinear, and dynamic physical systems governed by principles of thermodynamics and fluid dynamics.

Skills

Reinforcement Learning

Machine Learning

Deep Learning

Python

Data Science

Industrial Automation

Control Systems

Sensor Data Analysis

Problem-Solving

Collaboration

Communication

Phaidra

AI virtual plant operators for industrial efficiency

About Phaidra

Phaidra deploys artificial intelligence virtual plant operators to support operations teams in critical facilities. Their AI-powered control systems are designed to enhance stability, energy efficiency, and sustainability by learning and adapting over time. Unlike traditional static control systems that cannot adjust dynamically, Phaidra's technology continuously improves performance, addressing issues of degradation and lack of resiliency in industrial settings. The company has achieved notable success, such as delivering 40% energy savings at Google's data centers, and is expanding its solutions to various sectors, including pharmaceutical production and data centers. Phaidra's goal is to enhance operational efficiency and sustainability for its clients, generating revenue through the implementation and maintenance of its AI-driven systems.

Seattle, WashingtonHeadquarters

2019Year Founded

$41.3MTotal Funding

EARLY_VCCompany Stage

Industrial & Manufacturing, Energy, AI & Machine LearningIndustries

51-200Employees

Benefits

Health Insurance

Dental Insurance

Vision Insurance

Unlimited Paid Time Off

Parental Leave

Home Office Stipend

Company Equity

Risks

Increased competition from AI-driven industrial solutions providers could impact Phaidra's market share.

Rapid AI advancements may require Phaidra to continuously innovate, straining resources.

Potential data privacy concerns and regulatory scrutiny could challenge Phaidra's operations.

Differentiation

Phaidra offers AI solutions for mission-critical facilities, enhancing stability and efficiency.

The company combines AI expertise from Google-Deepmind with industry knowledge from Trane and Johnson Controls.

Phaidra's AI systems adapt and improve over time, unlike static, hard-coded control systems.

Upsides

Phaidra achieved 40% energy savings at Google's data centers, showcasing its effectiveness.

The rise of edge computing complements Phaidra's solutions for real-time analytics and efficiency.

Growing interest in AI-driven predictive maintenance aligns with Phaidra's focus on stability.

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