德国波茨坦气候影响研究所博士后职位

德国波茨坦气候影响研究所博士后职位

德国波茨坦气候影响研究所（The Potsdam Institute for Climate Impact Research, PIK）成立于1992年，是德国政府的科研机构，为国际上知名的气候变化研究单位。它对全球变化、气候影响和可持续发展等领域进行科学和社会学的研究，致力于探索地球系统的可承受性，提出人与自然可持续发展的相关战略。

Post-doctoral position (m/f/d)

Employer

Raven51 AG (Potsdam-Institut für Klimafolgenforschung e.V. (PIK))

Location

Potsdam, Brandenburg (DE)

Salary

a collective pay scheme and associated benefits as well as a subsidized travel card or Deutschland-T

Closing date

31 Oct 2024

Post-doctoral position (m/f/d) (Position number: 43-2024 Postdoc P2F) in the field of Machine Learning for Emulation of Earth system models, starting on 01.01.2025.

The position is funded for two years. Remuneration is in accordance with the German public tariff scheme (TV-L Brandenburg), salary group E 13. This is a full-time position with a weekly working time of 40 hours per week. Appointment is conditional on approval by the funding agency. The position can be filled on a part-time basis.

The position is funded via the Horizon Europe project “Past to Future: Towards fully plaeo-informed future climate projections”, which will start on January 1st 2025. This large EU project with 24 partners aims to advance Earth system models with regard to improved reproduction of climate variability as evidenced in paleoclimate proxy archives, including model re-calibrations and development of new, efficient model components also using machine learning approaches.

Key responsibilities:

Development of hybrid modelling approaches, combining physical model components with data-driven machine learning components

Contribution to the development of a new fast Earth system model designed for paleoclimate simulations

Development of differentiable Earth system model components

Development of efficient approaches to combine process-based with data-driven models

Requirements:

PhD in applied mathematics, machine learning, physics, meteorology or related field

Experience with machine learning methods is required

Experience in developing and running Earth system models is of advantage

Experience with paleoclimate proxy data and / or Earth system model simulations is of advantage

Please apply by 31.10.2024 directly using our application form.

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