PhD Fellow: Greenland Paleoceanography & Ice Sheet Melt

1000scholars

København

On-site

DKK 312,000 - 402,000

Full time

14 days+

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Job summary

GEUS is seeking a PhD fellow to reconstruct past Greenland Ice Sheet melt and North Atlantic ocean changes using marine sediment records. This 3-year position, within the Past2Risk project, starts 2027-01-01 in Copenhagen.

The role combines sedimentology, biomarkers, and palaeoceanography to quantify past glacier discharge and ocean variability. You will work with cores from Greenland fjords, develop quantitative reconstructions, and connect with modern observations to understand AMOC stability

Qualifications

  • MSc degree in geoscience.
  • Interest in Greenland Ice Sheet and North Atlantic climate variability and paleoclimate.
  • Experience with marine sedimentology, sediment-core analysis, geochronology, or proxy-data statistics is a plus.
  • Strong analytical and problem-solving skills; ability to develop quantitative reconstructions.

Responsibilities

  • Develop high-resolution reconstructions of Greenland Ice Sheet melt and ocean variability.
  • Work with marine sediment cores and proxies to reconstruct glacier discharge and water-mass conditions.
  • Link sediment records with modern observations (e.g., PROMICE) for a bridge to present-day variability.
  • Collaborate across disciplines within the Past2Risk project.

Skills

Analytical skills
Problem-solving
English communication
Collaborative work
Marine sedimentology
Geochronology
Paleoceanography

Education

MSc in Geoscience

Tools

Sediment-core analysis
Statistical analysis

Job description

GEUS is seeking a PhD fellow to reconstruct past Greenland Ice Sheet melt and North Atlantic ocean changes using marine sediment records. This 3-year position, within the Past2Risk project, starts 2027-01-01 in Copenhagen.

The role combines sedimentology, biomarkers, and palaeoceanography to quantify past glacier discharge and ocean variability. You will work with cores from Greenland fjords, develop quantitative reconstructions, and connect with modern observations to understand AMOC stability

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