Geophysical ML Engineer for Quantum Sensing — Melbourne

Nomad Atomics

Melbourne

Hybrid

AUD 120.000 - 180.000

Vollzeit

14 Tage+

Eine vollständige Bewerbung in einer Minute

Maßgeschneiderter Lebenslauf und Anschreiben – versandbereit.

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Benefits dieser Stelle

Employee share option package
Competitive salary

Zusammenfassung

Nomad Atomics in Melbourne, Australia is seeking an experienced geophysical modeller to help build Nomad’s geophysical modelling capabilities. You’ll work closely with the geophysics team and founders on end-to-end modelling, data analysis and real‑world applications of our sensors.

The role requires a strong background in numerical software, Monte Carlo methods and Bayesian statistics, with a PhD or Masters and a track record of solving complex real‑world problems.

Qualifikationen

  • Fast learner with strong problem-solving and curiosity.
  • Experience developing, testing and deploying numerical software.
  • Background in computational methods for data processing and modelling.

Aufgaben

  • Lead end-to-end geophysical modelling development for Nomad's sensors.
  • Build forward propagated models of real-world underground systems.
  • Implement best-practice and novel techniques for potential field inversion.
  • Analyse simulation outputs and perform statistical assessments.
  • Collaborate with geophysics team and founders on new applications.
  • Develop surveying techniques with deployment experts.

Kenntnisse

Python programming
Machine learning techniques
Bayesian statistics
Statistical analysis
Team communication

Ausbildung

Masters or PhD in geophysics or related field

Tools

Python
MATLAB
Numerical modelling tools

Jobbeschreibung

Nomad Atomics in Melbourne, Australia is seeking an experienced geophysical modeller to help build Nomad’s geophysical modelling capabilities. You’ll work closely with the geophysics team and founders on end-to-end modelling, data analysis and real‑world applications of our sensors.

The role requires a strong background in numerical software, Monte Carlo methods and Bayesian statistics, with a PhD or Masters and a track record of solving complex real‑world problems.

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