Finde einen Job 
Finde eine Ausbildung 
Top Arbeitgeber 
Top Universitäten 
Für Unternehmen Auf einen Blick
- Aufgaben: Join a team to develop machine learning methods for analyzing genetic networks.
- Arbeitgeber: EMBL Heidelberg is a leading research institution in molecular biology and genomics.
- Mitarbeitervorteile: Collaborate with top scientists, present at conferences, and contribute to impactful publications.
- Warum dieser Job: Work on cutting-edge research that combines computational skills with real-world applications in genetics.
- Gewünschte Qualifikationen: Ph.D. in relevant fields with strong programming skills in Python and experience in machine learning required.
- Andere Informationen: Opportunity to supervise students and research assistants while advancing your career in a dynamic environment.
Das voraussichtliche Gehalt liegt zwischen 42000 - 84000 € pro Jahr.
Home Postdoc Abroad Postdoctoral Researcher in Computational Genomics – EMBL Heidelberg, Germany
Postdoctoral Researcher in Computational Genomics : The research group of Oliver Stegle at EMBL Heidelberg is seeking a Postdoctoral Researcher to contribute to a collaborative project focused on applying machine learning and causal inference to decipher genetic networks from high-throughput perturbation data. The successful candidate will work within an interdisciplinary team to develop tailored methodologies for analyzing population-scale cohorts and perturbation screens, with a focus on gene regulation dynamics.
Postdoctoral Researcher in Computational Genomics – Causal Machine Learning for Gene Regulation
Designation: Postdoctoral Researcher
Research Area: Causal Machine Learning for Gene Regulation
Eligibility/Qualification: Candidates should hold a Ph.D. or equivalent qualification in computer science, statistics, mathematics, physics, engineering, or biological science with demonstrated experience in computational and statistical development. Strong programming skills in Python and experience with machine learning or statistical learning frameworks are required.
Job Description:
- Develop machine learning and causal inference methodologies for deciphering genetic networks from high-throughput perturbation data
- Collaborate with experimentalists and other computational scientists to analyze population-scale cohorts and perturbation screens
- Develop robust software solutions for data analysis and scale them to clinical applications
- Present results at conferences, contribute to publications, and participate in research proposal preparation
- Supervise and guide Research Assistants and Students
How to Apply: Interested applicants should submit their applications online through the EMBL website, including a cover letter and CV.
#J-18808-Ljbffr
Postdoctoral Researcher in Computational Genomics – EMBL Heidelberg, Germany Arbeitgeber: Zuhause In Duesseldorf
Kontaktperson:
Zuhause In Duesseldorf HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: Postdoctoral Researcher in Computational Genomics – EMBL Heidelberg, Germany
✨Tip Number 1
Familiarize yourself with the latest advancements in machine learning and causal inference, especially as they relate to genomics. This will not only help you understand the research group's focus but also allow you to engage in meaningful discussions during interviews.
✨Tip Number 2
Network with current or former researchers at EMBL Heidelberg. They can provide insights into the team dynamics and expectations, which can be invaluable when preparing for your application and potential interviews.
✨Tip Number 3
Showcase your programming skills in Python by contributing to open-source projects or creating your own projects related to computational genomics. This practical experience can set you apart from other candidates.
✨Tip Number 4
Prepare to discuss your previous research experiences in detail, particularly any collaborative projects. Highlight how you worked with interdisciplinary teams, as this is a key aspect of the role at EMBL.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: Postdoctoral Researcher in Computational Genomics – EMBL Heidelberg, Germany
Tipps für deine Bewerbung 🫡
Understand the Research Focus: Familiarize yourself with the research group's work, particularly in machine learning and causal inference related to genetic networks. This will help you tailor your application to highlight relevant experiences.
Craft a Strong Cover Letter: In your cover letter, clearly articulate your motivation for applying, your relevant skills in programming (especially Python), and any experience you have with machine learning or statistical frameworks. Make sure to connect your background to the specific requirements of the position.
Highlight Relevant Experience: When updating your CV, emphasize your Ph.D. qualifications and any relevant projects or publications that showcase your computational and statistical development skills. Include specific examples of your work with population-scale cohorts or perturbation data.
Follow Application Instructions: Ensure that you submit your application through the EMBL website as specified. Double-check that all required documents, including your cover letter and CV, are included and formatted correctly before submitting.
Wie du dich auf ein Vorstellungsgespräch bei Zuhause In Duesseldorf vorbereitest
✨Showcase Your Technical Skills
Be prepared to discuss your programming skills in Python and any experience you have with machine learning or statistical learning frameworks. Highlight specific projects where you've applied these skills, as this will demonstrate your capability to contribute to the research group's goals.
✨Understand the Research Focus
Familiarize yourself with the current projects of Oliver Stegle's group, especially those related to causal inference and genetic networks. Being able to discuss how your background aligns with their work will show your genuine interest and help you stand out.
✨Prepare for Collaborative Scenarios
Since the role involves collaboration with experimentalists and other computational scientists, think of examples from your past experiences where you successfully worked in interdisciplinary teams. This will illustrate your ability to communicate and collaborate effectively.
✨Discuss Your Research Impact
Be ready to talk about how your previous research has contributed to the field, including any publications or presentations. Emphasizing your ability to present results and engage with the scientific community will demonstrate your commitment to advancing knowledge in computational genomics.
