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7 дней назад

Junior Machine Learning Geoscientist (AI)

Формат работы
onsite
Тип работы
fulltime
Грейд
junior
Английский
b2
Страна
UK
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR

Junior Machine Learning Geoscientist (AI): Applying cutting-edge machine learning to subsurface geoscience challenges with an accent on AI/ML algorithm design, geological interpretation, and subsurface modeling. Focus on developing AI/ML algorithms to improve geological realism and validating predictive models.

Location: Onsite in Abingdon, United Kingdom

Company

hirify.global is one of the world’s largest providers of products and services to the global energy industry.

What you will do

  • Apply theories, principles, and practices to the research and development of new products, processes, and procedures.
  • Design and implement AI/ML algorithms to automate and enhance geological interpretation.
  • Develop AI/ML algorithms to improve geological realism in subsurface models.
  • Validate predictive models using blind test datasets and real-world scenarios.
  • Work closely with multidisciplinary colleagues to refine and enhance workflows.
  • Contribute to publications, patents, and technical presentations.

Requirements

  • Honors degree (2:1 or above) in geoscience.
  • 2 - 5 years relevant industry experience.
  • Strong understanding of specific geoscience domains such as stratigraphy, sedimentology, or petroleum geology.
  • Experience working with subsurface datasets (e.g., wireline, seismic, biostratigraphy).
  • Strong Python programming skills and experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
  • Excellent communication and teamwork skills in a collaborative R&D environment.

Nice to have

  • Proven application of AI/ML in geoscience projects.
  • Experience in the energy sector.

Culture & Benefits

  • Opportunities for innovation, achievement, growth, and leadership.
  • Investment in employee development and career empowerment.
  • Competitive compensation.
  • Work in a collaborative R&D environment.

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