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- Aufgaben: Join our team to develop and implement cutting-edge methods in probabilistic learning for big data.
- Arbeitgeber: Be part of the Karlsruhe Institute of Technology's innovative Scientific Computing Center.
- Mitarbeitervorteile: Enjoy flexible working hours, training opportunities, and a supportive team environment.
- Warum dieser Job: Contribute to impactful research while collaborating with experts in a dynamic and creative setting.
- Gewünschte Qualifikationen: PhD in relevant fields with strong skills in statistical learning and programming languages like Python or R.
- Andere Informationen: Position starts in August 2024; apply by 05.08.2024.
Das voraussichtliche Gehalt liegt zwischen 48000 - 72000 € pro Jahr.
Postdoctoral Research Fellow (f/m/d) in Probabilistic Learning and Methods for Big Data at the Karlsruhe Institute of Technology, Scientific Computing Center (SCC)
Focus on: Probabilistic Learning & Methods for Big Data
The Scientific Computing Center is the Information Technology Center of KIT. The newly established Research Group Methods for Big Data starting in August 2024 at the Scientific Computing Center welcomes applications for a postdoctoral research fellow (f/m/d).
In this project you will:
- Develop novel methods that leverage the potential of statistical learning and Bayesian (Deep) Learning.
- Investigate the theoretical properties of the developed algorithms.
- Implement the developed methods.
- Contribute to joint research inside the group.
- Publish the results at leading journals, workshops, and conferences.
Job requirements:
- Excellent university degree (master) and completed PhD in statistics, mathematics, data science, computer science, or similar programs.
- Expertise in at least one of the following areas: Statistical Learning, Bayesian (Deep) Learning, Uncertainty Quantification and Probabilistic Machine Learning, High-Dimensional Statistics, Distributional Regression, Causal Inference, Continual Learning, Hybrid Algorithms.
- Track record and excellent publications in at least one of the main research areas above.
- Strong computational and mathematical skills.
- Solid programming skills in any scientific programming language, e.g., Python, R.
- High proficiency in English, both written and spoken for your scientific publications and presentations.
- High degree of creativity, commitment, analytical competence, and interdisciplinary teamwork.
We offer you an exciting and varied job within an agile team as well as a wide range of training opportunities and flexible and family-friendly working time models. For more information about SCC as your new work home, please visit here .
We are looking forward to your application (Motivational letter, CV, Certificates)!
Salary: Category 13, depending on the fulfillment of professional and personal requirements.
Organizational unit: Scientific Computing Center (SCC)
Start date: ASAP
Duration: 3 years
Application deadline: 05.08.2024
Contact person in line-management: For further information, please contact Prof. Dr. Nadja Klein at
Application: Please apply online using the button below for this vacancy number 340/2024. Personnel Support is provided by Mr. Meschar, phone: +49 721 608-25029, Hermann-van-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany.
We prefer to balance the number of employees (f/m/d). Therefore, we kindly ask female applicants to apply for this job. Recognized severely disabled persons will be preferred if they are equally qualified.
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Postdoctoral Research Fellow (f/m/d) in Probabilistic Learning and Methods for Big Data the Kar[...] Arbeitgeber: The International Society for Bayesian Analysis
Kontaktperson:
The International Society for Bayesian Analysis HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: Postdoctoral Research Fellow (f/m/d) in Probabilistic Learning and Methods for Big Data the Kar[...]
✨Tip Number 1
Make sure to showcase your expertise in statistical learning and Bayesian methods during the interview. Prepare specific examples of your past work that demonstrate your skills in these areas, as they are crucial for this position.
✨Tip Number 2
Familiarize yourself with the latest research and publications in probabilistic machine learning and high-dimensional statistics. Being able to discuss recent advancements will show your passion and commitment to the field.
✨Tip Number 3
Highlight your programming skills, especially in Python or R, during discussions. Be ready to talk about specific projects where you implemented algorithms or developed methods, as practical experience is highly valued.
✨Tip Number 4
Demonstrate your ability to work in interdisciplinary teams by sharing experiences from previous collaborations. This role emphasizes teamwork, so showing that you can effectively communicate and collaborate with others will be beneficial.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: Postdoctoral Research Fellow (f/m/d) in Probabilistic Learning and Methods for Big Data the Kar[...]
Tipps für deine Bewerbung 🫡
Understand the Role: Make sure you thoroughly understand the responsibilities and requirements of the Postdoctoral Research Fellow position. Familiarize yourself with the focus areas such as Probabilistic Learning and Big Data methods.
Craft a Strong Motivational Letter: In your motivational letter, clearly articulate your research interests and how they align with the group's focus. Highlight your expertise in statistical learning, Bayesian methods, or any relevant area, and mention your previous publications.
Highlight Relevant Experience: In your CV, emphasize your academic background, including your PhD and any relevant research experience. Include specific projects or algorithms you've developed that relate to the job description.
Proofread Your Application: Before submitting, carefully proofread your motivational letter and CV for any errors. Ensure that your English is clear and professional, as strong communication skills are essential for this role.
Wie du dich auf ein Vorstellungsgespräch bei The International Society for Bayesian Analysis vorbereitest
✨Showcase Your Research Experience
Be prepared to discuss your previous research projects in detail, especially those related to statistical learning and Bayesian methods. Highlight any publications or presentations you've made, as this demonstrates your ability to contribute to the group's research goals.
✨Demonstrate Technical Proficiency
Make sure to showcase your programming skills, particularly in languages like Python or R. You might be asked to solve a problem or explain how you would implement a specific algorithm, so brush up on your coding skills and be ready to think on your feet.
✨Emphasize Interdisciplinary Collaboration
The role requires a high degree of teamwork. Be ready to discuss examples of how you've successfully collaborated with others in past projects. This could include working with researchers from different fields or contributing to joint publications.
✨Prepare for Theoretical Questions
Since the position involves investigating theoretical properties of algorithms, expect questions that test your understanding of key concepts in probabilistic machine learning and high-dimensional statistics. Brush up on these topics to confidently answer any theoretical inquiries.
