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- Aufgaben: Join our team to research Bayesian learning and spatial clustering models.
- Arbeitgeber: Humboldt-Universität Berlin is a leading institution in research and education.
- Mitarbeitervorteile: Full-time position with opportunities for career development and collaboration with international experts.
- Warum dieser Job: Contribute to cutting-edge research while expanding your skills in a vibrant, diverse environment.
- GewĂĽnschte Qualifikationen: PhD in Statistics or related field; strong background in Bayesian methods and programming required.
- Andere Informationen: Encouraging applications from women and individuals with diverse backgrounds.
Das voraussichtliche Gehalt liegt zwischen 45000 - 60000 € pro Jahr.
Open position as Postdoctoral Researcher in Bayesian statistical learning and spatial regression at HU Berlin
Feb 2, 2022
Postdoctoral Research fellow with full-time employment – E 13 TV-L HU (third-party funding, limited 12 months but extension possible).
Job description: The working group of Statistics and Data Science at Humboldt-Universität Berlin invites applications for a position to contribute to the research on statistical aspects of Bayesian learning and novel methods towards high-dimensional spatial clustering models. The position can be associated with Prof. Klein’s Emmy Noether group funded by the German Research foundation (DFG). Opportunities for own scientific qualification (career development) are provided.
Requirements: Completed Master and PhD (preferably with very good marks) in Statistics, Mathematics, or related field with specialisation in Statistics, Data Science or Mathematics; a strong background in the following fields: Bayesian computational methods, spatial models and inference therein, variational inference, density regression. Furthermore, a thorough mathematical understanding; substantial experience in scientific programming with R, Matlab, Python, C/C++ or similar; very good communication skills and team experience, proficiency of the written and spoken English language (German is not obligatory).
We offer: A unique environment of researchers and leading international experts in the fields. The vibrant international network includes established collaborations in Singapore and Australia. The position offers potential to closely work with several applied sciences.
Application process: Please send your application (including a CV with list of publications, a motivational statement (at most one page) explaining the applicant’s interest in the position as well as their relevant skills and experience, copies of degrees/university transcripts, names and email addresses of at least two professors that may provide letters of recommendation) within 4 weeks, to the Humboldt-Universität zu Berlin, School of Business and Economics, Prof. Dr. Nadja Klein, Unter den Linden 6, 10099 Berlin or preferably as a single PDF file to
Contact: For further information please contact the project leader Prof. Dr. Nadja Klein ( ).
Diversity statement: HU is seeking to increase the proportion of women in research and teaching, and specifically encourages qualified female scholars to apply. Severely disabled applicants with equivalent qualifications will be given preferential consideration. People with an immigration background are specifically encouraged to apply. Since we will not return your documents, please submit copies in the application only.
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Open position as Postdoctoral Researcher in Bayesian statistical learning and spatial regressio[...] Arbeitgeber: The International Society for Bayesian Analysis
Kontaktperson:
The International Society for Bayesian Analysis HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: Open position as Postdoctoral Researcher in Bayesian statistical learning and spatial regressio[...]
✨Tip Number 1
Make sure to highlight your experience with Bayesian computational methods and spatial models during any interviews or networking opportunities. This will show that you have the specific expertise they are looking for.
✨Tip Number 2
Engage with current research in Bayesian statistical learning and spatial regression. Familiarize yourself with recent publications from Prof. Klein’s group to demonstrate your genuine interest and knowledge during discussions.
✨Tip Number 3
Network with professionals in the field by attending relevant conferences or workshops. This can help you make connections that might lead to recommendations or insights about the position.
✨Tip Number 4
Prepare to discuss your programming skills in R, Matlab, Python, or C/C++. Be ready to provide examples of projects where you've applied these skills, as practical experience is highly valued.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: Open position as Postdoctoral Researcher in Bayesian statistical learning and spatial regressio[...]
Tipps für deine Bewerbung 🫡
Understand the Job Requirements: Carefully read the job description to understand the specific qualifications and skills required for the position. Highlight your relevant experience in Bayesian computational methods, spatial models, and scientific programming.
Craft a Strong Motivational Statement: Write a motivational statement (maximum one page) that clearly explains your interest in the position and how your skills and experiences align with the research focus of Prof. Klein’s group. Be specific about your background in statistics and data science.
Prepare Your CV and Publications List: Ensure your CV is up-to-date and includes a list of your publications. Tailor your CV to emphasize your academic achievements, relevant projects, and any experience in high-dimensional spatial clustering models.
Gather Recommendation Contacts: Identify at least two professors who can provide strong letters of recommendation. Make sure to include their names and email addresses in your application, as this will strengthen your candidacy.
Wie du dich auf ein Vorstellungsgespräch bei The International Society for Bayesian Analysis vorbereitest
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Bayesian computational methods and spatial models. Highlight specific projects where you've applied these techniques, and be ready to explain your approach and the outcomes.
✨Demonstrate Your Communication Abilities
Since very good communication skills are a requirement, practice explaining complex statistical concepts in simple terms. This will show that you can effectively communicate with both technical and non-technical team members.
✨Prepare for Teamwork Questions
Expect questions about your experience working in teams. Think of examples where you collaborated successfully, especially in research settings, and how you contributed to achieving common goals.
✨Express Your Interest in Career Development
The position offers opportunities for scientific qualification. Be ready to discuss your career aspirations and how this role aligns with your goals, showing that you are motivated to grow within the field.
