Research Scientist (PhD)
TLDR
Develop forecasting and decision models for satellite link conditions, benchmark them against physics-based baselines, and turn research into code the platform team can ship.
The Role
We are looking for a PhD-level Research Scientist to build the models behind ConstellationOS. You will develop forecasting and decision models for satellite link conditions and ground-network operations, and prove them against real data and physics-based baselines. Your work shows up in customer pilots and government evaluations.
Responsibilities
Develop and train machine learning models that forecast link conditions and support operational decisions.
Own data acquisition and preprocessing for telemetry, weather, atmospheric, and RF datasets.
Benchmark learned models against deterministic physics models and report results honestly, including failures.
Do simulation research for GNC and RF systems.
Work with academic groups and publish or present results
Turn research into code the platform team can ship.
Requirements
Ph.D. (or near completion) in Machine Learning, Applied Mathematics, Physics, Aerospace, Electrical Engineering, or a related field.
Publications or equivalent research output in forecasting, deep learning, reinforcement learning, or scientific ML.
Strong Python and PyTorch or JAX. Able to write research code others can run.
Experience with time-series, signal, or physical-system data is a plus.
U.S. person required (ITAR).
Benefits
Equity Compensation
0.5% – 1.5%
Constellation Space develops ConstellationOS, an innovative AI-driven platform designed to enhance the operation and resilience of satellite networks. Targeting leading space companies, it offers advanced predictive capabilities for link conditions and autonomous network management, ensuring seamless and reliable data transmission in a rapidly evolving landscape.
- Founded
- Founded 2025
- Employees
- 1-10 employees
- Industry
- Diversified Telecommunication Services
- Total raised
- $6.5M raised
- Last funding
- Raised April 2026