Practical trainings, student assistants and theses

Optimization of fitting procedures in surface complexation models (Id 416)

Student practical training / Student Assistant / Volunteer internship

Production of electricity by nuclear power plants inevitably generates high-level and long-lived radioactive waste. A solution considered by several nuclear waste management agencies is to store them into deep underground repositories. The principle of such a concept is to provide a multi-barrier system to avoid the release of the radioactive waste through the biosphere for very long time scales (up to hundred thousand of years). It is thus of great importance to be able to characterize both at a macroscopic and a molecular level the different processes (retention, reduction, surface precipitation, etc.) that can take place onto mineral surfaces and thus affect the availability and the mobility of the radionuclides. This information can be inserted in surface complexation models for the description and prediction over a long time-scale of the interaction of pollutants at the solid/liquid interface with several sorbent surfaces. These surface complexation models rely on a thermodynamic description of the solid/water interface and represent a geochemically robust and sound approach to quantify adsorption equilibria.

The solution of adsorption equilibria problems can be reached via Gibbs Free Energy Minimization and/or Law of Mass Action. Standard procedures apply commonly used geochemical software such as FITEQL/PHREEQC coupled to shell optimizers (UCODE, PEST). They are nevertheless subject to numerical instability and/or convergence problems, and to the risk to fall into a local minimum region rather than a global optimum valley. This risk is drastically increased when the number of adjustable parameters becomes higher than 3 or 4. Also the “trial and error” approach within the numerical fitting data can become very fast time consuming.

Thus, the objective of the present work are i) to develop alternative approaches to enable the handling of a high number of adjustable parameters at once, ii) the speed up of the optimizing procedure in order to reduce the time required for the user to reach a satisfactory description of the experimental data.

Your specific tasks:

  • Implement a genetic algorithm coupled to Levenberg-Marquardt optimization on a high performance computing cluster,
  • Compare the results of with another optimization path, namely Downhill Simplex,
  • Find reliable ways to provide realistic uncertainties of the adjustable parameters (e.g. scale sensitivity, Monte-Carlo, etc.).

This internship or assistant position can be used as a basis for a follow-up Research Project, Bachelor or Master thesis.

Department: Surface Processes

Contact: Dr. Jordan, Norbert, Dr. Kelling, Jeffrey

Requirements

Good knowledge in python programming and standard optimization routines (Newton-Raphson, Levenberg-Marquardt, etc.) is mandatory.

Students without knowledge in chemistry are also encouraged to apply.

Very good English skills are appreciated.

Conditions

Duration min. 3 months

Start: from now

Workplace: HZDR, Dresden-Rossendorf

Online application

Please apply online: english / german

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Unterstützung im Rechnungswesen (Id 408)

Student Assistant

Die Abteilung Finanzen, Finanzcontrolling und Drittmittel ist für das Finanzmanagement des Helmholtz-Zentrum Dresden-Rossendorf verantwortlich. Im Bereich Rechnungswesen (Haupt-, Banken-, Debitoren-, Kreditoren- und Anlagenbuchhaltung) wird Ihre Hilfe benötigt.

Ihre Aufgaben:

  • Unterstützung (SAP) bei der Erfassung von Geschäftsvorfällen
  • Unterstützung (SAP) bei der Stammdatenpflege, insbesondere Kreditoren
  • Sonstige Unterstützungstätigkeiten

Department: Finance, Financial Controlling and Third-party Funds

Contact: Hartwig, Patrick

Requirements

  • Begonnenes Studium der Wirtschaftswissenschaften
  • Erste Kenntnisse in den Grundlagen des Rechnungswesens (Buchführung, Kosten- und Leistungsrechnung)
  • Selbstständige und verantwortungsvolle Arbeitsweise

Conditions

  • Arbeitsbeginn ab sofort
  • Mindestens 6 Monate
  • Tätigkeitsort: Standort Dresden-Rossendorf

Wir bieten Ihnen die Möglichkeit, im Studium Erlerntes praxisnah umzusetzen! Es erwarten Sie ein
motiviertes und kollegiales Arbeitsumfeld, tatkräftige Unterstützung bei der Umsetzung Ihrer Aufgaben sowie spannende Einblicke in die finanztechnische Schaltzentrale unseres Forschungsstandortes.

Online application

Please apply online: english / german

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Student internship, research assistant, school practical training, master/diploma thesis, compulsory internship (Id 407)

School practical training / Student practical training / Bachelor theses / Master theses / Diploma theses / Student Assistant / Holiday job / Compulsory internship / Volunteer internship / Research Assistant

At Helmholtz-Zentrum Dresden-Rossendorf (HZDR), over 1,500 employees from more than 70 nations are conducting cutting-edge research in the fields of ENERGY, HEALTH, and MATERIALS to address the major challenges facing society today.
The Center for Advanced Systems Understanding (CASUS), founded in Görlitz in 2019, is a German-Polish interdisciplinary research center focusing on data-intensive digital systems.
CASUS offers student internships in a wide range of scientific fields. You are welcome to apply and join CASUS if you are interested in gaining knowledge in the following research areas:

  • Theoretical Chemistry
  • Earth System Science
  • Matter under Extreme Conditions
  • Systems Biology
  • Digital Health
  • Computational Radiation Physics
  • Computational Quantum Many-Body Theory
  • Mathematical Foundations of Complex System Science
  • Dynamics of Complex Living Systems
  • Machine Learning for Infection and Disease
You can also apply to join our administrative team as a student assistant.

Institute: CASUS

Contact: Dr. Mir Hosseini, Seyed Hossein, Mazur, Weronika, Dr. Calabrese, Justin, Dr. Martinez Garcia, Ricardo, Dr. Bussmann, Michael, Dr. Cangi, Attila, PD Dr. Kuc, Agnieszka Beata, Dr. Yakimovich, Artur, Dr. Knüpfer, Andreas

Requirements

  • Student in computer science, physics, chemistry, or related fields
  • Student already enrolled at the university in Germany, Poland or Czech Republic (close exchange and attendance in the office preferable and combined with the moblie working from Germany combinable)
  • Eager to learn new skills
  • Strong motivation to work in a collaborative environment
  • Preliminary experience in code development is an advantage
  • Excellent communication skills in English and/or German or Polish

Conditions

  • A vibrant research community in an open, diverse and international work environment
  • Scientific excellence and extensive professional networking opportunities
  • A wide range of qualification opportunities
  • We support a good work-life balance with the possibility of part-time employment, mobile working and flexible working hours
  • Either an immediate start or a start in 2024 is possible
Please submit your application (including a one-page cover letter, CV, academic degrees, transcripts, etc.) online on the HZDR application portal

Online application

Please apply online: english / german

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Numerical simulation of particles in rising gas bubbles (Id 356)

Student practical training / Master theses / Student Assistant / Compulsory internship / Volunteer internship

The separation of aerosol particles by a moving gas-liquid fluidic interface is central to a wide variety of industrial and natural applications, among which stand out air purification systems and precipitation scavenging. The particle size significantly affects the separation rate. The diffusion of particles in the nanometer range is largely dominated by molecular diffusion. In this regime, predictive models accurately estimate the separation rates. Model inaccuracy increases, however, significantly when the particle size ranges from 0.1 μm to 2.5 μm. In this impaction-dominated regime, the complex interplay between the flow dynamics on both sides of the fluidic interface and the particle inertia makes it difficult to develop suitable models.
In this work, the student will numerically investigate whether enforcing bubble deformation into a non-spherical shape leads to a higher deposition rate, hereby making the particle separation process more efficient. The results will lead to the development of an improved and reliable separation model accounting for the deformation of the fluidic interface and the associated flow changes.

Department: Experimental Thermal Fluid Dynamics

Contact: Maestri, Rhandrey

Requirements

  • General interest in fluid mechanics
  • Preliminary experience in code development (C++) is desirable
  • Good written and oral communication skills in either English or German

Conditions

  • Either an immediate start or a start in 2024 is possible
  • Duration of the internship is anticipated to be 6 months but can be modified according to study regulations
  • Remuneration according to HZDR internal regulations

Online application

Please apply online: english / german

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