Post-Doctoral Research Visit F/M Postdoctoral Researcher Position: AI Research for Climate Change and Environmental Sustainability

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Le descriptif de l’offre ci-dessous est en Anglais

Type de contrat : CDD

Contrat renouvelable : Oui

Niveau de diplôme exigé : Thèse ou équivalent

Autre diplôme apprécié : PhD required

Fonction : Post-Doctorant

Contexte et atouts du poste

The INRIA team, ARCHES: AI Research for Climate Change and Environmental Sustainability is currently accepting applications for a postdoctoral researcher. This position is located at INRIA Paris.

About ARCHES

ARCHES: AI Research for Climate Change and Environmental Sustainability is focused on using AI to address climate change, and to enable environmentally sustainable solutions. Understanding and addressing climate change is an urgent challenge. Meanwhile, the study of climate change is an extremely data-rich field, especially considering not only the rapidly growing amount of satellite retrievals but also the massive amounts of simulation output from physics-driven climate models, providing a lens into the distant past and distant future. The founding members of ARCHES have pursued a research vision that machine learning can shed light on and help in confronting climate change. Their research helped spawn the interdisciplinary field of Climate Informatics which was recognized as a key research priority in The World Economic Forum's report on AI for the Earth, in 2018.

 

 

 

Mission confiée

 The position 

We are open to postdoctoral candidates with a strong grounding in machine learning research, and experience (or at least a significant interest) in applications to climate change and environmental sustainability. Candidates are encouraged to submit a research statement with proposed work on topics of mutual interest with members of ARCHES. In particular, ARCHES research is focused along three axes:

  1. AI for Climate Change Adaptation – Forecasting and informing near-term decisions (e.g., weather prediction with a focus on extreme events)
  2. AI for Climate Change Mitigation – Forecasting and informing mid-term decisions (e.g., accelerating the green energy transition)
  3. AI for Understanding Climate Change Impacts – Projecting long-term impacts (e.g., sea-level rise, carbon cycle)
  4. Advances in core AI - New research in machine learning in computer vision. ARCHES members have demonstrated that climate and environmental applications open new questions for the design and analysis of machine learning algorithms. We have also found that applied research can yield unorthodox twists, even on standard machine learning techniques, which in turn spark interest in the machine learning research community.

Principales activités

  1. Review existing literature in both machine learning and the application domain
  2. Design and implement pipelines that include machine learning for the application
  3. Design and conduct empirical studies using the learned models for the application, and comparison to state-of-the-art
  4. Prepare, submit for publication, present, and disseminate research findings
  5. Serve as a research mentor for doctoral students on related projects

Compétences

Technical skills and level required :

  • Candidate must hold a PhD in Computer Science (Informatique), statistics, mathematics, or related fields
  • Machine learning, data mining, statistics, and/or AI coursework and/or projects
  • Familiarity with modern machine learning / deep learning software, tools, pipelines

Languages :

  • Written competency in English
  • Oral competency in English or French

 

Avantages

  • Subsidized meals
  • Partial reimbursement of public transport costs
  • Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
  • Teleworking and flexible organization of working hours
  • Professional equipment available (videoconferencing, loan of computer equipment, etc.)
  • Social, cultural and sports events and activities
  • Access to vocational training
  • Social security coverage