EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of additively manufactured Mg alloys for biodegradable implant applications

Helmholtz-Zentrum hereon GmbH - Geesthacht

Your tasks

You focus on developing your PhD project In silico optimization of PBF-LB-manufactured Mg alloys. There is a plethora of studies on the processing, mechanical and corrosion properties of Mg-based alloys, mostly limited to the alloys produced via traditional casting, extrusion and forging. Reports on rationalisation of processing-structure-property relationships (PSPR) additively manufactured (PBF-LB) Mg alloys are still scarce. In the meantime, the variation of processing parameters (laser power, spot size, hatch distance, scanning speed, layer thickness, scan strategy and subsequent heat-treatment) has a significant effect on the microstructure (grain size, alloying elements distribution, crystallographic texture), mechanical properties (hardness, yield and tensile strength) and corrosion profile (rate and localization). This work focuses on machine learning-assisted PSPR optimization of recently developed lean Mg-0.1 Ca alloy produced by PBF-LB. After identification of the most relevant parameters adopting a design of experiments strategy, a probabilistic (e.g. Gaussian Process Regression) model to describe the relationship between process parameters and material properties will be developed and subsequently exposed to Bayesian optimization to find the optimal set of parameters that improve process performance and material quality. Secondly, different machine learning strategies based on traditional supervised learning techniques (e. g. random forest (RF), artificial neural network (ANN)) will be applied using the parameters of strongest influence on the target properties. Moreover, the obtained data will be fed into a generative pre-trained transformer model (e. g. ChatGPT) to probe the potential of in-context learning for process optimization. The robustness of the model is assessed by experimental validation. The objectives are i) to produce Mg-0.1 Ca alloy at varying PBF-LB fabrication process parameters (at Uppsala Universitet), collect experimental data on microstructure, mechanical and corrosion properties; ii) determine, using sensitivity analysis, impact of the individual process parameters on the target properties and develop predictive machine learning model; iii) based on the machine learning algorithms, develop PBF-LB Mg alloy with defined microstructure, improved mechanical and corrosion properties. Research stays are planned at: Uppsala Universitet, Sweden, and Quintus Technologies AB, Västerås, Sweden Supervisors: Dr. Christian Feiler, Dr. Sviatlana Lamaka, Prof. Mikhail Zheludkevich https://www.hereon.de/institutes/surface_science/index.php.en

Your profile

To be eligible as a MSCA (Marie Skłodowska-Curie Actions) doctoral candidate, you must i) not have a doctoral degree at the date of recruitment, ii) not be enrolled in a doctoral program, and iii) comply with a mobility rule requiring you to not have resided or carried out your main activity (work, studies, etc.) in the host country (Germany) for more than 12 months in the 36 months prior to recruitment (i.e. this includes online activities). Requirements:
Master’s degree and documented experience and knowledge in either of the following: materials science, biomedical engineering, chemistry, chemical engineering, materials engineering, engineering physics, applied mathematics, computational materials science or a related field, or other education considered equivalent to these qualifications.
We require good oral and written skills in English. Additional qualifications:
It is advantageous to have experience in one or more of the following areas:

• Machine Learning & Bayesian optimization (Python, Supervised learning, Multi-objective optimization)
• Additive manufacturing of metals
• Corrosion characterization
• Mechanical testing

Great emphasis is put on personal qualities such as the ability to independently plan and carry out work. You have a good ability to work towards set goals and you work focused to achieve them. In this, you have an ability to focus, even during periods of high workload. You have good communication skills, where through this quality you cooperate well with others. You also have a good ability to write academic texts. Your application must include:

• A short cover letter (up to 1 page) in which you describe yourself, why you want to do a PhD and why you are suitable for this position.
• CV (max 2 pages)
• A certified copy of your master's degree and your course grades.
• Copies (or drafts) of your master's thesis and other documents, such as publications, that you wish to refer to.
• Names and contact details of at least two contact persons who have accepted to be references for you. It must also be stated what relationship you have had with the respective referent.

The application should be written in English.

We offer you

PhD students employed through the Marie Sklodowska Curie Doctoral Network will receive a salary in accordance with the Marie Curie regulations for doctoral candidates for the time of their fellowship (36 months). Taking into account the living allowance (with the coefficient of 101.2% for Germany), mobility and family allowances (when eligible) and subtracting the employer contributions, the gross salary in Germany is 3719,13 eur/month (or 4233,93 eur/month with family allowance if eligible). Social security contributions and income tax will be deducted from this gross salary before payment of the net salary to the doctoral candidate. This employment is a temporary position. Scope of employment 100%. Starting date March 1^st, 2026 or as agreed upon. Placement: Geesthacht (near Hamburg), Germany. For further information about the position, please contact:
Christian Feiler, +49 4152 87‑2125

Severely disabled persons and those equaling severely disabled persons who are equally suitable for the position will be considered preferentially within the framework of legal requirements.