Academic Researcher (f/m/d) in Applied Geosciences

Karlsruhe Institute of Technology (KIT)

Eggenstein-Leopoldshafen

Presencial

EUR 52.000 - 70.000

Jornada completa

14 días+

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Ventajas ofrecidas por este puesto de trabajo

Flexible working hours
Remote-work options
30 days annual leave

Descripción de la vacante

Karlsruhe Institute of Technology (KIT) invites applications for a research position within the MALEG 4.0 project. The role focuses on generating and processing hydrogeochemical data from field experiments, using an emulator of power plant processes, and evaluating results with machine learning algorithms.

You will work on data acquisition, database management, model validation, and transferring insights into a Digital Chemical System.

Formación

  • Master’s degree in Applied Geosciences, Computational Earth Sciences, Informatics or related field.
  • Very good written and spoken English; German language skills preferred.
  • German driving license (class B) preferred.
  • Background in database management (SQL).
  • Programming skills (Python, MATLAB, C/C++).
  • Experience in data analysis and machine learning.
  • Interest in geothermal and geochemical applications.

Responsabilidades

  • Being part of the MALEG 4.0 project to improve geothermal power plant efficiency.
  • Automated generation and processing of hydrogeochemical data from field experiments with an emulator.
  • Data evaluated using machine learning algorithms.
  • Data acquisition and database management.
  • Data processing for machine learning applications.
  • Model validation, benchmarking and transfer.
  • Establishing a Digital Chemical System.
  • Workflow integration into MALEG emulator.
  • Possibility for a PhD position.

Conocimientos

Programming (Python/MATLAB/C/C++)
Data analysis & ML
SQL / Database
English language
German (prefer)

Educación

Master’s degree in Applied Geosciences, Computational Earth Sciences, Informatics or related field

Descripción del empleo

  • Being part of the MALEG 4.0 project (BMWE, FKZ 020E-100743476), the efficiency of geothermal power plants is being improved
  • This requires the automated generation and processing of hydrogeochemical data generated by field experiments involving an emulator (twin of the power plant processes)
  • The data is evaluated using machine learning algorithms
  • Data acquisition and database management
  • Data processing for machine learning applications
  • Model validation, benchmarking and transfer
  • Establishing a Digital Chemical System
  • Workflow integration into MALEG emulator
  • Possibility for a PhD position
Your Tasks
  • Being part of the MALEG 4.0 project (BMWE, FKZ 020E-100743476), the efficiency of geothermal power plants is being improved
  • This requires the automated generation and processing of hydrogeochemical data generated by field experiments involving an emulator (twin of the power plant processes)
  • The data is evaluated using machine learning algorithms
  • Data acquisition and database management
  • Data processing for machine learning applications
  • Model validation, benchmarking and transfer
  • Establishing a Digital Chemical System
  • Workflow integration into MALEG emulator
  • Possibility for a PhD position
Your Responsibilities Include
  • Being part of the MALEG 4.0 project (BMWE, FKZ 020E-100743476), the efficiency of geothermal power plants is being improved
  • This requires the automated generation and processing of hydrogeochemical data generated by field experiments involving an emulator (twin of the power plant processes)
  • The data is evaluated using machine learning algorithms
  • Data acquisition and database management
  • Data processing for machine learning applications
  • Model validation, benchmarking and transfer
  • Establishing a Digital Chemical System
  • Workflow integration into MALEG emulator
  • Possibility for a PhD position
Your Profile
  • Master’s degree in Applied Geosciences, Computational Earth Sciences, Informatics or related field
  • Very good written and spoken English and preferably German language skills
  • Preferably a German driver’s license (class B)
  • Background in database management (e.g. SQL)
  • Programming skills (e.g. Python, MATLAB, C/C++)
  • Experience in data analysis and machine learning
  • Interest in geothermal and geochemical applications
We Offer
  • Science for Impact : Engage with topics of societal relevance—in an excellent scientific environment that enables change.
  • Flexible Working Hours : Take advantage of flexible‑hours schemes, remote‑work options, and a 30‑day annual leave entitlement to achieve an optimal work‑life balance.
  • Career‑Building and Developmental Opportunities : We provide you with a structured onboarding program, a broad spectrum of continuing‑education options, and personalised support, thereby fostering your individual growth.
  • Family-friendliness : The “KIT‑Family+” program assists you in reconciling work and family life by offering childcare services, holiday activities, a parent‑child office space, and assistance with caring for relatives.
  • Stay Healthy : Under the motto “Fit at KIT – Body, Mind and Soul,” we promote your well‑being through fitness classes and mental‑health programmes.
  • Individualised Extra Benefits : Enjoy a corporate pension (VBL), a €25 monthly contribution toward a JobTicketBW, plus a broad selection of cultural and recreational programmes.
Job location

Karlsruhe (and Eggenstein-Leopoldshafen)

Salary

Salary category 13 TV-L; classification is based on personal and professional qualifications.

Contract duration

3 years

Contact person in line-management

Dr. Lars Yström

lars.ystroem@kit.edu

Dr. Fabian Nitschke

fabian.nitschke@kit.edu

If you have general questions about the application process, please contact

Raquel Carrasco Sanchez

Personalservice (PSE)

raquel.carrasco@kit.edu

+49 721 608-42016

At KIT we value the diversity of our employees; different perspectives and backgrounds enrich our work. We therefore welcome applications from all candidates. Women are especially encouraged to apply. Applications from recognized severely disabled individuals are given preferential consideration when qualifications are equal.

Application up to:

2026-10-31

Job posting number:

1215/2026

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