Auf einen Blick
- Aufgaben: Join our team to develop web apps and manage data pipelines in life sciences.
- Arbeitgeber: Leibniz-HKI focuses on natural product research and infection biology.
- Mitarbeitervorteile: Work with cutting-edge tech in a dynamic, international team; competitive salary.
- Warum dieser Job: Make an impact in life science data analysis while growing your skills.
- Gewünschte Qualifikationen: Degree in computer science or bioinformatics; experience with R/Python and server management required.
- Andere Informationen: Encouraging applications from diverse backgrounds; rolling application review.
Das voraussichtliche Gehalt liegt zwischen 36000 - 60000 € pro Jahr.
Job Description
Job Advertisement\\n Leibniz-HKI-05/2025\\n\\nThe Leibniz Institute for Natural Product Research and Infection Biology ( Leibniz-HKI ) investigates the pathobiology of human-pathogenic fungi and identifies targets for the development of novel natural product-based antibiotics. The research group Microbiome Dynamics invites talented and highly gifted candidates to apply as\\n\\nSoftware Engineer (m/f/div)\\n\\n\\n\\nThe research group Microbiome Dynamics (MDB) is seeking a highly skilled software engineer with a keen eye and interest in solving exciting life science problems. Given the high demand for big data analysis applications in the life sciences, our demand for hardware and software solutions towards efficient, high-performance computation increases constantly.
In the recent past, we significantly upgraded our computer hardware to match our current demands. On top of that, we reach out to the community whenever possible and encapsulate our services into pipelines and web applications. Both our hardware and software require constant monitoring and maintenance.\\n\\nTo ensure the fulfilment of our goals, we welcome applications from software and IT specialists with the following expertise:\\n\\n Your profile:\\n\\nUniversity degree in computer science, bioinformatics, or a comparable field\\nExperience in accessing server units through command-line, as well as developing / maintaining analysis pipelines in containerized environments, is a must\\n\\nProficiency in R and/or Python for pipeline and web application development, as well as big data analysis\\n\\nInterest in life science data science, including gene expression and microbiome data analysis, is a plus\\nKnowledge of statistical methods in the context of biological systems is a plus\\n\\nYour tasks:\\n\\nIn collaboration with our team, the tasks to be addressed by the software engineer comprise:\\nWeb app development and maintenance\\nCuration of pipelines dedicated to efficient, high-throughput data preprocessing and analysis\\nCluster management / server administration\\nDistributed computing / software scaling towards grid engines\\nMonitoring / work load surveillance of our HPCs\\n\\n\\nWe offer:\\n\\nThe software engineer will be hosted in the research group Microbiome Dynamics (MBD) of Prof.
Dr. Gianni Panagiotou of the Leibniz-HKI in an international, dynamic team with access to state-of-the-art computational resources.\\n\\nRemuneration will be according to the TV-L (Collective Agreement for the Public Service of the Federal States, unrestricted, full-time) at the salary level E10. Depending on qualifications, adjustments are possible.
As an equal opportunity employer, the Leibniz-HKI is committed to increasing the percentage of female scientists and therefore especially encourages them to apply.\\n\\n\\nFor further information:\\n\\nProf. Dr. Gianni Panagiotou | +49 3641 532-1759 | career@hki-jena.de\\n\\nApplications:\\n\\nLeibniz-HKI is proud to be an equal opportunity employer and promote diversity and inclusion in the workplace.
It aims to increase the proportion of underrepresented groups in case of equal suitability. All qualified persons, regardless of color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, or other classification protected by law will receive consideration for employment.\\nComplete applications in English should include a cover letter, a CV containing a complete list of publications, a brief statement of research experiences, and the addresses of two possible referees and should be submitted via the \\nLeibniz-HKI online application system\\n\\n. The deadline for the advertisement is February 28, 2025 , but applications will be reviewed on a rolling basis.\\n\\n\\nLeibniz Institute for Natural Product Research and Infection Biology\\n Adolf-Reichwein-Straße 23 | 07745 Jena
Software Engineer (m/f/div) Arbeitgeber: Leibniz-Institut für Naturstoff-Forschung und Infektionsbiologie e. V. - Hans-Knöll-Institut (HKI) /
Kontaktperson:
Leibniz-Institut für Naturstoff-Forschung und Infektionsbiologie e. V. - Hans-Knöll-Institut (HKI) / HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: Software Engineer (m/f/div)
✨Tip Number 1
Familiarize yourself with the specific technologies and tools mentioned in the job description, such as R, Python, and containerized environments. Being able to discuss your experience with these technologies during the interview will demonstrate your suitability for the role.
✨Tip Number 2
Show your passion for life sciences by staying updated on recent developments in microbiome research and data analysis. This knowledge can help you engage in meaningful conversations with the team and showcase your genuine interest in their work.
✨Tip Number 3
Prepare to discuss your experience with high-performance computing (HPC) and server management. Highlight any relevant projects where you successfully managed or optimized computational resources, as this is a key aspect of the role.
✨Tip Number 4
Network with professionals in the field of bioinformatics and life sciences. Attend relevant conferences or workshops to meet potential colleagues and learn more about the latest trends, which can give you an edge in your application.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: Software Engineer (m/f/div)
Tipps für deine Bewerbung 🫡
Understand the Job Requirements: Make sure to thoroughly read the job description and understand the specific skills and experiences required for the Software Engineer position. Highlight your proficiency in R and/or Python, as well as your experience with command-line server access and containerized environments.
Craft a Tailored Cover Letter: Write a cover letter that specifically addresses how your background and skills align with the tasks mentioned in the job description. Emphasize your interest in life science data science and any relevant projects you've worked on.
Prepare Your CV: Ensure your CV is up-to-date and includes a complete list of publications, relevant work experiences, and technical skills. Make it easy to read and highlight your achievements in software development and data analysis.
Gather References: Identify two referees who can speak to your qualifications and experiences. Make sure to include their contact information in your application, as this will be an important part of the selection process.
Wie du dich auf ein Vorstellungsgespräch bei Leibniz-Institut für Naturstoff-Forschung und Infektionsbiologie e. V. - Hans-Knöll-Institut (HKI) / vorbereitest
✨Show Your Technical Skills
Be prepared to discuss your experience with R and Python in detail. Highlight specific projects where you've developed analysis pipelines or web applications, and be ready to explain the challenges you faced and how you overcame them.
✨Demonstrate Your Interest in Life Sciences
Since the role involves life science data science, express your enthusiasm for the field. Share any relevant experiences or projects related to gene expression or microbiome data analysis to show that you are genuinely interested in the subject matter.
✨Prepare for Problem-Solving Questions
Expect questions that assess your problem-solving abilities, especially in high-performance computing and server management. Think of examples from your past work where you successfully managed workloads or optimized processes.
✨Ask Insightful Questions
Prepare thoughtful questions about the research group's current projects and future goals. This shows your interest in the team and helps you understand how you can contribute effectively to their objectives.