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- Aufgaben: Develop and implement lectures on Machine Learning and Deep Learning.
- Arbeitgeber: Join Graz University of Technology, a leading institution in engineering and science.
- Mitarbeitervorteile: Enjoy a friendly atmosphere, remote work options, and access to top research infrastructure.
- Warum dieser Job: Engage in exciting interdisciplinary projects and contribute to impactful research.
- Gewünschte Qualifikationen: Must have a doctoral degree in Computer Science or related fields.
- Andere Informationen: We encourage qualified women and diverse applicants to apply.
Das voraussichtliche Gehalt liegt zwischen 69060 - 96684 € pro Jahr.
Responsibilities
- Development and implementation of lectures in the area of Machine Learning, Deep Learning and Reinforcement Learning
- Scientific publication activity and participation in scientific conferences
- Collaboration in the preparation of research proposals
- Collaboration in interdisciplinary projects at the institute and preparation of project reports
- Collaboration in the organization of scientific conferences & workshops at the institute
Profile
Admission Requirements
- Doctoral degree in Computer Science, or equivalent fields of study
Desired Qualification
- Publication activity in the field of machine learning and AI.
- Research activity in the field of brain-inspired machine learning.
- Research at the interface of machine learning and symbolic AI.
We Offer
- Interesting area of responsibility
- Collegial and friendly working atmosphere
- International training and teaching opportunities
- Seal of quality for in-house advancement of women
- Award for being the most family-friendly company in Styria 2018
- Subsidy for public transport
- University’s sports program
- Shopping Discounts
- Workplace Health Management
- Top research infrastructure and access to the latest technologies
- Exciting opportunities for professional and personal development
- Safe and stable working environment
- Possibility for home office
We offer an annual gross salary of at least € 69,060.60 for a full-time position. An overpayment based on qualification and experience is possible.
Graz University of Technology aims to increase the proportion of women, in particular in management and academic staff, and therefore qualified female applicants are explicitly encouraged to apply. Preference will be given to women if applicants are equally qualified.
Graz University of Technology actively promotes diversity and equal opportunities. Applicants are not to be discriminated against in personnel selection procedures on the grounds of gender, ethnicity, religion or ideology, age, sexual orientation (Anti-discrimination).
People with disabilities and who have the relevant qualifications are expressly invited to apply.
Organisational Unit
The Institute of Theoretical Computer Science was founded in 1992 to research fundamental problems in information processing, such as the design of computer algorithms, the complexity of computations and computational models, automatic knowledge acquisition (machine learning), the complexity of learning algorithms, pattern recognition with artificial neural networks, computational geometry and information processing in biological neural systems. Its research integrates methods from mathematics, computer science and computational neuroscience. In teaching, the institute is responsible for courses and seminars that introduce students to the basic techniques and results of theoretical computer science. In addition, it offers advanced courses, seminars and applied computing projects in computational geometry, complexity theory, machine learning and neural networks.
About us
Graz University of Technology is the longest-established university of technology in Austria. Here, successful teams of students, talented up-and-coming scientists, ambitious researchers and a lively start-up scene enjoy an inspirational environment as well as access to top-quality equipment. And all this in one of the most innovative and livable regions in Europe. TU Graz offers an inspiring working environment with outstanding infrastructure and service-oriented university management.
Contact
Graz University of Technology
Dean of the Faculty of Computer Science and Biomedical Engineering
For further questions, please contact Robert Legenstein, (no applications). Please note that we only accept applications submitted via our online application portal. Applications by e-mail or post will not be considered.
Become part of the team of Graz University of Technology – we are looking forward to your application!
Job details
Title
Graz University of Technology is an important university in the international research and education network of engineering and science.
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Postdoctoral Researcher (m/f/d) in Machine Learning, Deep Learning, Group Legenstein Arbeitgeber: Karlstad University
Kontaktperson:
Karlstad University HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: Postdoctoral Researcher (m/f/d) in Machine Learning, Deep Learning, Group Legenstein
✨Tip Number 1
Make sure to highlight your publication activity in machine learning and AI during the interview. Discuss specific papers you've authored or co-authored, and how they relate to the research interests of the group led by Robert Legenstein.
✨Tip Number 2
Prepare to discuss your experience with interdisciplinary projects. Be ready to share examples of how you've collaborated with researchers from different fields, as this is a key aspect of the role at Graz University of Technology.
✨Tip Number 3
Familiarize yourself with the latest trends in brain-inspired machine learning and symbolic AI. Being able to discuss current advancements and how they can be applied in your research will demonstrate your passion and knowledge in the field.
✨Tip Number 4
Engage with the academic community by attending relevant conferences or workshops before your application. Networking with professionals in the field can provide valuable insights and potentially lead to recommendations that strengthen your application.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: Postdoctoral Researcher (m/f/d) in Machine Learning, Deep Learning, Group Legenstein
Tipps für deine Bewerbung 🫡
Understand the Role: Make sure to thoroughly read the job description for the Postdoctoral Researcher position. Understand the responsibilities and desired qualifications, especially in machine learning and AI, to tailor your application effectively.
Highlight Relevant Experience: In your CV and cover letter, emphasize your doctoral research, any publications in machine learning or AI, and relevant projects. Showcase your experience with interdisciplinary collaboration and scientific conferences.
Craft a Strong Cover Letter: Write a personalized cover letter that connects your background and research interests with the goals of Graz University of Technology. Mention specific projects or experiences that align with their focus on brain-inspired machine learning and symbolic AI.
Follow Application Guidelines: Ensure you submit your application through the online portal as specified. Double-check that all required documents are included and formatted correctly before hitting submit.
Wie du dich auf ein Vorstellungsgespräch bei Karlstad University vorbereitest
✨Showcase Your Research Experience
Be prepared to discuss your previous research projects in detail, especially those related to machine learning and AI. Highlight any publications you have contributed to and how they align with the institute's focus on brain-inspired machine learning.
✨Demonstrate Collaboration Skills
Since collaboration is key in this role, share examples of how you've successfully worked in interdisciplinary teams. Discuss any experience you have in preparing research proposals or organizing scientific conferences, as these are important aspects of the job.
✨Prepare for Technical Questions
Expect technical questions related to machine learning, deep learning, and reinforcement learning. Brush up on the latest technologies and methodologies in these fields, and be ready to discuss how you would implement them in your lectures and research.
✨Express Your Passion for Teaching
As part of the responsibilities includes developing lectures, convey your enthusiasm for teaching and mentoring students. Share any previous teaching experiences and your approach to making complex topics accessible and engaging.
