Overview

AI Research Scientist (ML for Physical Systems) atPhaidra. Join to apply for the AI Research Scientist (ML for Physical Systems) role at Phaidra.Phaidra is building the future of industrial automation. We create AI-powered control systems for the industrial sector, enabling facilities to automatically learn and improve over time. Our team focuses on reinforcement learning to convert raw sensor data into high-value actions and decisions, with domain experts configuring AI agents without writing code.Who You Are

Research Scientists lead our efforts in developing novel algorithmic architectures for intelligent control systems in the industrial sector. You have a PhD, post-doc, or professorial background and a deep expertise in machine learning and physical systems (thermodynamics, fluid mechanics, control systems). You combine ML with a principled approach to model, optimize, and control complex physical processes.You will work with expertise from machine learning, reinforcement learning, optimization, and control theory, applying groundbreaking research to real-world industrial problems. We seek a team member located within the UK (preferred), USA, or Canada.Responsibilities

Collaborate with AI researchers on applied real-world problems to demonstrate algorithmic feasibility and enhance capabilities.Design and implement prediction and control algorithms for complex, nonlinear, dynamic physical systems governed by thermodynamics and fluid dynamics.Develop and maintain a benchmarking platform for algorithmic performance evaluation and experimental design.Present research findings clearly and efficiently, both internally and externally, verbally and in writing.Participate in and organize ambitious collaborative research projects.Work with external collaborators and maintain relationships with relevant research labs and key individuals.Mentor and guide Research Engineers to apply research findings to industrial domains.Key Qualifications

PhD in mechanical engineering, chemical engineering, control systems, applied physics, or related field, with expertise in thermodynamics, fluid mechanics, or dynamic system modeling and control.Strong foundation in machine learning and software engineering; proficiency in Python and open-source ML libraries (Keras, TensorFlow, PyTorch, scipy, scikit-learn, numpy, pandas, ray).1+ years of applied research experience.Experience with research projects and contributions to open-source software.Alignment with company values: curiosity, ownership, transparency and directness, outcome-based performance, and customer empathy.Preferred Skills and Experience

Relevant experience to the position.Proven track record of publications.Experience applying AI to real-world scenarios.Our Stack

PythonPyTorch, scipyKubernetes, Docker, RayGCPOnboarding and Growth

In your first 30 days: onboarding program, meet the research team, learn how teams operate, read the handbook, set up development environment.By your first 60 days: understand Phaidra, build relationships, understand research tracks, plan first project.By your first 90 days: fully integrated, contribute to knowledge sharing, project in full swing with early results.General Interview Process

Interviews via Google Meet with several team members and founders; camera required.Compensation and Benefits

Base salary by region: US residents, Canada residents, UK residents (ranges provided in the original description).Equity included. Benefits vary by region and are described in the full posting.Employment and Policy Notes

Remote-friendly, 100% remote with international hiring via OysterHR; US E-Verify notice as applicable; equal opportunity employer statements retained.Note:

This posting adheres to the information provided in the original description and preserves EEO and compliance statements.

#J-18808-Ljbffr