Your personal sphere of play:
- Conduct and publish high-quality, theory-driven, and empirically rigorous research in the field of international business with a focus on family firm internationalisation, with the objective of contributing to leading international peer-reviewed journals.
- Build and consolidate an independent research profile in international business, with a particular focus on family firm internationalization, and actively contribute to advancing scholarly debates in this area.
- Be actively involved in research projects and scientific studies at the Institute of International Business, especially in the areas of network embeddedness, family firms, and internationalization processes.
- Apply and further develop qualitative research methods (e.g., interviews, case studies, archival research) in the design, execution, and dissemination of international business research.
- Actively collaborate in the research activities of the institute and contribute to the further development of its research agenda under the direction of Univ.-Prof. Maria Emmanouela Plakogiannaki, PhD.
- Participate in the acquisition, implementation, and dissemination of third-party funded research projects, including the preparation of competitive research grant applications.
- Develop an independent academic profile and engage in international scholarly networks, conferences, and workshops.
- Contribute to teaching in international business–related courses at the bachelor’s and master’s levels, including course preparation, delivery, assessment, and student supervision.
- Supervise bachelor’s and master’s theses and support doctoral researchers in the area of international business.
- Participate in organizational and administrative tasks related to research, teaching, and academic self-governance of the Department and Faculty.
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Long Description
- Support and advice for researchers and students with regard to data access and processing
- Managing data access
- Documenting how data is used by researchers and students
- Advising and assisting researchers in the areas of research data management and open science, including support in creating data management plans, organizing data, and preparing data for publication in appropriate repositories
- Designing and developing innovative discipline-specific services in the area of Research Data Management
- Building awareness for sustainable Research Data Management
- Developing workflows, policies and standards for Research Data Management
- Designing and delivering needs-based training on Research Data Management and Open Science
- Conducting needs assessments among the faculty
- Networking in university, national and international initiatives
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Tasks:
- Contribute to the strategic development of the dataTUdiscovery service center in a leading role, including interfaculty cooperation, innovation in AI methodologies, and integration with TU Wien’s digital research ecosystem
- Collaborate with domain researchers based on incoming dataTUdiscovery service center projects across faculties to translate scientific questions into AI-based approaches and co-develop research solutions
- Analyze and interpret scientific data and domain-specific requirements from chemistry, physics, materials science, and/or mathematics to design appropriate AI/ML models and guide methodological choices
- Develop reusable and reproducible AI models, workflows, and software components, contributing to TU Wien’s open research infrastructure (e.g. TU Wien Cookbooks)
- Co-author publications of research results in peer-reviewed journals and potentially present outcomes at international venues to enhance TU Wien’s visibility in Research and AI
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Tasks:
- Contribute to the strategic development of the dataTUdiscovery service center in a leading role, including interfaculty cooperation, innovation in AI methodologies, and integration with TU Wien’s digital research ecosystem
- Collaborate with domain researchers based on incoming dataTUdiscovery service center projects to transform scientific problems into robust computational workflows, including data preprocessing, model selection, and validation
- Develop reusable AI models, workflows, and software components, contributing to TU Wien’s open research infrastructure (e.g. TU Wien Cookbooks)
- Ensure reproducibility, versioning, documentation, and deployment of AI/ML tools using best-practice software engineering, e.g., Continuous Integration and Delivery, containerization, model lifecycle management
- Co-author publications of research results in peer-reviewed journals and potentially present outcomes at international venues to enhance TU Wien’s visibility in Research and AI
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