Öffentlicher Dienst: PhD Student (f/m/d) Machine Learning for Modelling Complex Geochemical Systems / Completed university studies (Master/Diploma) in the field of Chemistry, Chemical Engineering, Environmental Chemistry, Data Sciences, Geosciences or related … in Dresden, Sachsen von gesucht

ÖFFENTLICHER DIENST: PhD Student (f/m/d) Machine Learning für Modellierung komplexer geochemischer Systeme in Dresden

Das Helmholtz-Zentrum Dresden-Rossendorf (HZDR) sucht einen PhD Student (f/m/d), um moderne Machine Learning-Techniken zur Modellierung komplexer geochemischer Systeme zu erforschen. Mit einem engagierten Team von etwa 1.500 Mitarbeitern setzt sich das HZDR für die Bewältigung gesellschaftlicher Herausforderungen in den Bereichen Energie, Gesundheit und Materie ein.

Die Forschung der Abteilung für Thermodynamik von Actiniden konzentriert sich auf die Entwicklung von Methoden zur Risikominderung, die durch technische Prozesse entstehen, insbesondere im Hinblick auf radioaktive Abfälle. Die Position bietet die Möglichkeit zur Teilzeitarbeit, passend zum Lebensstil vieler Studierender.

Ihre Aufgaben

In dieser Rolle unterstützen Sie die Entwicklung von Surrogatmodellen, die es ermöglichen, die extrem hohen Rechenanforderungen bei der Modellierung geochemischer Systeme zu umgehen. Ihre Hauptaufgaben umfassen:

Identifikation modernster ML-Methoden zur Anwendung auf geochemische Systeme
Bewertung dieser Methoden hinsichtlich Nachvollziehbarkeit und Robustheit
Implementierung vielversprechender Algorithmen zur Modellierung der Migration von Radionukliden in kristallinen Gesteinen
Durchführung von Proof-of-Concept-Simulationen und Risikobewertungen

Ihr Profil

Um erfolgreich zu sein, sollten Sie ein abgeschlossenes Studium (Master/Diplom) in Chemie, Chemieingenieurwesen, Umweltchemie, Geowissenschaften oder ähnlichen Bereichen vorweisen können. Erfahrung in Machine Learning und hervorragende Programmierkenntnisse in Python, R oder Julia sind ebenfalls erforderlich.

Unser Angebot

Das HZDR bietet eine lebendige Forschungsumgebung mit zahlreichen Networking-Möglichkeiten sowie eine strukturierte Doktorandenprogramm. Sie profitieren zudem von einem attraktiven Gehalt nach TVöD-Bund, 30 Tagen Urlaub und flexiblen Arbeitszeiten.

Wenn Sie Teil eines innovativen und internationalen Teams werden möchten, freuen wir uns auf Ihre Bewerbung!

Zur kompletten Jobbeschreibung … *

Jobtitel

PhD Student (f/m/d) Machine Learning for Modelling Complex Geochemical Systems / Completed university studies (Master/Diploma) in the field of Chemistry, Chemical Engineering, Environmental Chemistry, Data Sciences, Geosciences or related …

Unternehmen

Vollständige Stellenbeschreibung

Offer DescriptionArea of research:PHD ThesisPart-Time Suitability:The position is suitable for part-time employment.Starting date:01.03.2026Job description:PhD Student (f/m/d) Machine Learning for Modelling Complex Geochemical SystemsWith cutting-edge research in the fields of ENERGY, HEALTH and MATTER, around 1,500 employees from more than 70 nations at Helmholtz-Zentrum Dresden-Rossendorf (HZDR) are committed to mastering the great challenges facing society today.The Institute of Resource Ecology performs research to protect humans and the environment from hazards caused by pollutants resulting from technical processes that produce energy and raw materials.The Department of Thermodynamics of Actinides is looking for a PhD Student (f/m/d) – Machine Learning for Modelling Complex Geochemical Systems. The job posting is subject to approval of the associated third-party funded project.Your tasksYou will help modelling complex geochemical systems, which are typically limited by extremely high computational demands. To break this bottleneck and cut simulation time by orders of magnitude, you will design and implement surrogate models that learn the behavior of full-physics codes using modern machine-learning techniques. These surrogates will be tuned for rapid, uncertainty-aware predictions and integrated into decision-support tools for deep geological repositories of nuclear waste-one of the most pressing challenges facing modern societies.Specifically, the tasks are:# Identify state-of-the-art machine-learning (ML) methods that can be applied to geochemical systems in geological contexts
# Assess these methods for traceability, robustness, and physicochemical correctness
# Implement and adapt the most promising algorithms to model radionuclide migration in crystalline host rocks
# Execute proof-of-concept ML simulations and perform a risk analysis of the resulting model outputs
# Present your scientific results at conferences, workshops, and seminars, and publish the work in peer-reviewed journals
# Collaborate with project partners at CASUS (HZDR), TU Bergakademie Freiberg, and TU DarmstadtYour profile# Completed university studies (Master/Diploma) in the field of Chemistry, Chemical Engineering, Environmental Chemistry, Data Sciences, Geosciences or related field
# Possess a solid background in geochemical processes (e.g., sorption, speciation, radionuclide transport)
# Complement the chemical expertise with some experience in machine-learning or data-analytics tools
# High-level programming skills (Python, R, Julia) to build, test, and optimize models of geochemical systems
# Interest in large-scale computational simulations (e.g., reactive transport, sorption processes)
# Capability to work in a structured, solution-oriented manner, demonstrating analytical thinking and a strong commitment to project goals
# Motivation to work collaboratively in an interdisciplinary and international team-oriented environment
# Excellent communication skills in EnglishOur offer# A vibrant research community in an open, diverse and international work environment
# Scientific excellence and extensive professional networking opportunities
# A structured PhD program with a comprehensive range of continuing education and networking opportunities – more information about the PhD program at the HZDR can be found here
# Salary and social benefits in accordance with the collective agreement for the public sector (TVöD-Bund) including 30 days of paid holiday leave, company pension scheme (VBL)
# We support a good work-life balance with the possibility of part-time employment, mobile working and flexible working hours
# Numerous company health management offerings
# Employee discounts with well-known providers via the platform Corporate Benefits
# An employer subsidy for the „Deutschland-Ticket Jobticket“We look forward to receiving your application documents (including cover letter, CV, diplomas/transcripts, etc.), which you can submit via our online-application-system.This research center is part of the Helmholtz Association of German Research Centers. With more than 42,000 employees and an annual budget of over € 5 billion, the Helmholtz Association is Germany’s largest scientific organisation.Where to apply E-mailpersonal@hzdr.de WebsiteRequirementsAdditional InformationWebsite for additional job detailsWork Location(s)Number of offers available 1 Company/Institute Helmholtz-Zentrum Dresden-Rossendorf – HZDR – Helmholtz Association Country Germany City Dresden GeofieldContact CityDresden WebsiteStreetBautzner Landstraße 400 Postal Code01328 E-Mailkontakt@hzdr.de Phone+49 351 260-0 Fax+49 351 269-0461STATUS: EXPIREDShare this page