Job Information
Organisation/Company: Silesian University of Technology
Research Field: Technology » Other; Computer science » Other; Mathematics; Engineering
Researcher Profile: First Stage Researcher (R1)
Positions: Master Positions
Application Deadline: 18 Oct 2026 - 23:59 (Europe/Warsaw)
Country: Poland
Type of Contract: Temporary
Job Status: Full-time
Offer Starting Date: 1 Nov 2026
Is the job funded through the EU Research Framework Programme? Horizon Europe - MSCA
Is the Job related to staff position within a Research Infrastructure? No
Offer Description
Project:
Towards an Understanding of Artificial Intelligence via a transparent, open and explainable perspective.
MARIE Skłodowska-CURIE Actions – MSCA Doctoral Network
Grant Agreement No. 101168344
Position: Doctoral Candidate – full-time, 12-month position
Research Target: Trustworthy and Reliable AI for Cyber-physical Systems
Deadline: 18 October 2026
Expected Start Date: 1 November 2026
How to Apply: tuai@polsl.pl (see more details for ”How to Apply Section”)
Host Institutions: Potential host institutions include:
- Silesian University of Technology (SUT), Poland
- Western Norway University of Applied Sciences (HVL), Norway
- Norwegian University of Science and Technology (NTNU), Norway
- Universidad Politécnica de Madrid (UPM), Spain
- University of Oviedo (UNIOVI), Spain
- University of Naples Federico II (UNINA), Italy
The final host institution and supervisor will be determined following the joint recruitment and selection process, taking into account:
- the candidate's scientific profile and research interests;
- the candidate's previous education and research experience;
- the alignment of the proposed research with the objectives and tasks of WP5;
- the available supervisory capacity within the consortium;
- the candidate's MSCA-DN mobility eligibility for the selected host country.
The selected candidate will therefore be matched with the TUAI partner offering the best scientific and supervisory fit.
Project Overview: The TUAI project aims to train the next generation of AI experts at the cutting edge of technology, addressing both advanced AI techniques and their application to real-world challenges.
The project focuses on the development of trustworthy, transparent, open and explainable Artificial Intelligence methods and their application in complex and dynamic environments. The TUAI consortium brings together universities and research institutions from several European countries together with industrial partners, providing an interdisciplinary and international research and training environment.
The selected Doctoral Candidate will contribute to the research and training activities of Work Package 5 (WP5), addressing research challenges related to Trustworthy and Reliable Cyber-physical Systems.
Eligibility Criteria
- Must NOT have lived or carried out your main activity (work, studies, etc.) in the country of the host institution for more than 12 months in the 3 years prior to the date of recruitment in accordance with the MSCA-DC program.
- Have a Master’s degree in a relevant field (e.g. Artificial Intelligence, Computer Science, Data Science, Mathematics, Engineering or related disciplines).
- Demonstrate scientific and technical knowledge as evidenced by publications (if applicable) or successful projects in line with the job description.
- Familiar with the latest in AI trends and models for development and with experience applying these models to practical applications for real-world challenges.
- Good programming skills, Python is mandatory, other languages (e.g., Java, C++) will be considered a plus to apply.
- Understand ML/DL frameworks such as TensorFlow and PyTorch.
- Familiar with version control systems such as Github, Git, etc.
- TOEFL, IETLS or other certificates that can prove your English level.
Remuneration
The successful candidate will receive remuneration in accordance with the MSCA Doctoral Network rules. The remuneration consists of a living allowance and a mobility allowance, with a family allowance where applicable. The living allowance is adjusted by the country correction coefficient applicable to the country of the final host institution. As the final host institution for DC14 will be determined through the joint TUAI recruitment and selection process, the applicable remuneration will be confirmed at the time of appointment. The final gross remuneration will therefore depend on the country of the selected host institution and the applicable MSCA correction coefficient, as well as the candidate's individual eligibility for the family allowance. Applicable deductions, including taxes and social security contributions, will be made in accordance with the legislation of the host country.
Additional Benefits
- International research collaboration and environment: Within the TUAI project, you can collaborate with many excellent researchers from different countries, nationalities and genders, which can help you advance your academic career.
- Industry experience: You can participate in industry projects to carry out real-world applications in different fields and sectors.
- Friendly research environments: You will enjoy research phenomena to collaborate with all the many friendly partners and supervisors.
- Responsible supervisors: All supervisors are responsible for their supervised students and have strong motivation to work together on high-level publications.
How to Apply
Interested applicants should prepare the following documents and send them directly to tuai@polsl.pl with the subject: “TUAI-last Name” (e.g. TUAIJordan). Please note that all documents should be in English only.
- A detailed CV with contact information, photo, gender and nationality. Educational qualifications should also be included, starting with a Bachelor's degree. Relevant professional experience (e.g., internship, project). Programming skills (certifications are desired, if applicable) should be included. It is recommended to list your academic publications (if applicable) and patents (if applicable). The file format is: CV_LastName.pdf (e.g., CV_Jordan.pdf).
- A motivation letter with maximum 1 page (e.g., movivation_Jordan.pdf)
- Education certifications (Bachelor, Master) (e.g., education_Jordan.pdf)
- Transcript with grades (Bachelor, Master) (e.g., transcript_Jordan.pdf)
- 3 reference letters (reference_Jordan.pdf). One letter MUST be from the Master supervisor.
- Master Thesis (if applicable) (thesis_Jordan.pdf)
- English certificates (if applicable) or something relevant materials to proof language skills (language_Jordan.pdf)
The candidate will NOT be considered for the positions if any items 1-6 are missing. All files should be compressed as a zip file (TUAI-Jordan.zip). Candidates are responsible for ensuring that all information is true and correct, otherwise the position will be canceled if documents or information are not correct.
Selection Process
Applicants with strong and relevant experience in CV will be considered for the following two stages evaluations.
The selection will be conducted through a transparent and merit-based joint TUAI recruitment process.
Stage 1 – Eligibility and qualification screening: applications will be assessed against the formal MSCA-DN eligibility requirements and the scientific and technical requirements of the position.
Stage 2 – Scientific evaluation and interview: shortlisted candidates will be invited to an online interview to discuss their academic background, research interests, motivation and potential contribution to WP5.
Stage 3 – Candidate–host matching: the final host institution and supervisor will be determined based on the candidate's scientific profile and research interests, the alignment with WP5, and available supervisory capacity within the consortium.
Application Conditions and Equal Opportunity
The specified nationality and gender are used for statistical purposes and are not used as evaluation criteria for the positions. We ensure equal opportunities within our workforce. This information will be treated in strict confidence and will not be used in any discriminatory way. All applications are considered impartially and without discrimination on the basis of nationality, ethnicity, skin color, gender, sexual orientation, gender identity, marital status, religion, age or disability.
Applications are reviewed on an ongoing basis until the position is filled. The selection process is carried out by an evaluation committee that follows guidelines designed to ensure equal opportunities for all applicants. The main criterion for selection is the match between the applicant’s qualifications and expertise and the specified requirements. Female applicants are particularly encouraged to apply, as gender balance is taken into account during the evaluation process to promote the representation of women in science and research.
Where to apply
E-mail: tuai@polsl.pl
Requirements
Skills/Qualifications
- A strong academic background in Artificial Intelligence, Computer Science, Data Science, Mathematics, Engineering or a related discipline, with an interest in AI applied to complex and safety-critical systems.
- Good knowledge of Machine Learning and Deep Learning methods, including experience with model development, training and evaluation.
- Programming skills in Python and experience with relevant AI/ML frameworks such as PyTorch, TensorFlow or equivalent tools.
- Knowledge or demonstrated interest in trustworthy, explainable and reliable AI, including aspects such as transparency, robustness, interpretability and resilience of AI-based systems.
- Knowledge or demonstrated interest in anomaly detection, real-time data analysis and/or predictive modelling, particularly for dynamic and safety-critical environments.
- Interest in AI sustainability, including resource efficiency, scalability, adaptability and the practical deployment of AI solutions.
- Understanding or interest in cyber-physical systems, industrial systems, critical infrastructures or other safety-critical applications will be considered an advantage.
- Knowledge or interest in AI security, adversarial robustness, fault tolerance or runtime verification will be considered an advantage.
- Ability to analyse scientific literature, formulate research questions and conduct independent scientific research.
- Ability to work in an interdisciplinary and international research team and collaborate with academic and industrial partners.
- Good written and spoken English.
Specific Requirements
Interested applicants should prepare the following documents and send them to tuai@polsl.pl with the subject: “TUAI DC14 – Last Name” (e.g., “TUAI DC14 – Jordan”). All documents must be submitted in English.
- A detailed CV including contact information, nationality, educational qualifications (starting with a Bachelor's degree), relevant academic and/or professional experience, programming skills, publications (if applicable), and patents (if applicable). File format: CV_LastName.pdf (e.g., CV_Jordan.pdf).
- A motivation letter, maximum 1 page. File format: Motivation_LastName.pdf.
- Copies of educational certificates (Bachelor's and Master's degrees or equivalent). File format: Education_LastName.pdf.
- Academic transcripts including grades for Bachelor's and Master's studies. File format: Transcript_LastName.pdf.
- Three reference letters, including at least one letter from the Master's thesis supervisor. File format: References_LastName.pdf.
- Master's thesis, if applicable. File format: Thesis_LastName.pdf.
- Evidence of English language proficiency, if applicable, such as an English language certificate or other relevant documentation. File format: Language_LastName.pdf.
- Mobility information for the previous 36 months, indicating the countries and periods of residence and/or main activity (e.g., employment, studies, research). Table Country | From | To | Residence and/or main activity | Institution/Employer. This information is required to assess eligibility under the MSCA-DN mobility rule, as the final host institution for DC14 will be determined through the joint selection process. File format: Mobility_LastName.pdf.
- Information on current doctoral studies, if applicable, including the doctoral programme, institution, research topic and supervisor. Current PhD students may apply provided that they do not hold a doctoral degree at the time of recruitment and their research can be aligned with the objectives of WP5. File format: PhD_Status_LastName.pdf.
The candidate will not be considered for the position if any of the mandatory documents listed above are missing. All documents should be combined into a single ZIP file named TUAI-DC14-LastName.zip.
Candidates are responsible for ensuring that all information provided is complete, accurate and truthful. Incorrect or misleading information may result in exclusion from the recruitment process or cancellation of the appointment.
Additional Information
Additional comments
Application Conditions and Equal Opportunity
The specified nationality and gender are used for statistical purposes and are not used as evaluation criteria for the positions. We ensure equal opportunities within our workforce. This information will be treated in strict confidence and will not be used in any discriminatory way. All applications are considered impartially and without discrimination on the basis of nationality, ethnicity, skin color, gender, sexual orientation, gender identity, marital status, religion, age or disability.
Applications are reviewed on an ongoing basis until the position is filled. The selection process is carried out by an evaluation committee that follows guidelines designed to ensure equal opportunities for all applicants. The main criterion for selection is the match between the applicant’s qualifications and expertise and the specified requirements. Female applicants are particularly encouraged to apply, as gender balance is taken into account during the evaluation process to promote the representation of women in science and research.
Work Location(s)
Number of offers available: 1
Company/Institute: Silesian University of Technology
Country: Poland
State/Province: Gliwice
City: Gliwice
Postal Code: 44-100
Contact
City: Gliwice
Website: http://www.polsl.pl
Street: Akademicka 2A
Postal Code: 44-100
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