• Pipeline Development: Design, implement, and optimize state-of-the-art bioinformatics pipelines for the analysis of multi-omics datasets, including genomics, metagenomics, transcriptomics, proteomics, and metabolomics. Applications include strain characterization, biomarker discovery, community composition analysis, and functional annotation.
• Data Management: Establish and maintain robust data management systems to ensure the integrity, reproducibility, and accessibility of large-scale datasets. Implement best practices for data storage, curation, and version control to enable seamless integration with machine learning workflows.
• IT Infrastructure: Design, establish, and manage high-performance computing (HPC) clusters or cloud-based infrastructure to support computational workflows. Ensure the scalability, performance, and reliability of the IT environment to meet the growing demands of data processing and analysis.
• Machine Learning Readiness: Develop and preprocess datasets to ensure they are optimized for machine learning applications. Collaborate with data scientists to design and implement AI-based solutions for biotics discovery, leveraging advanced algorithms to identify novel candidates and actionable insights.
• Advanced Analytics: Perform comprehensive analysis and integration of multi-omics data, applying statistical and computational methods to uncover patterns, correlations, and biological insights. Utilize predictive modeling and network analysis to support hypothesis-driven research.
• Automation of Experimental Data Analysis: Support scientists in automating analyses for flow cytometry, microscopy, and other molecular biology results. Develop computational workflows and tools that maximize the value of experimental data, enabling high-throughput and reproducible analyses.
• Collaboration: Partner with cross-functional teams, including microbiologists, data scientists, and product development teams, to design experiments, interpret findings, and propose innovative solutions. Act as a bioinformatics subject matter expert to guide decision-making processes.
• Innovation: Stay at the forefront of bioinformatics and omics research by integrating cutting-edge tools, methodologies, and technologies. Propose innovative approaches to accelerate the discovery and development of microbiome-based solutions.
• Reporting and Communication: Prepare and deliver comprehensive reports and presentations to communicate findings effectively to internal stakeholders and external collaborators. Translate complex bioinformatics results into actionable recommendations.
• Reproducibility and Documentation: Ensure reproducibility and transparency of all analyses by employing workflow management tools, version control systems, and thorough documentation. Promote best practices for bioinformatics workflows across the team.
• Mentorship: Provide guidance and mentorship to other team members, fostering a culture of continuous learning and innovation within the bioinformatics team.

• Education: Master's or PhD in bioinformatics, biostatistics, computer science, microbiology, or a related field.
• Experience: At least 5+ years of professional experience in bioinformatics, with a proven track record of developing and implementing pipelines and managing large-scale datasets in a multidisciplinary environment.
• Technical Expertise: Proficiency in programming languages such as Python, R, and Bash, with experience in workflow management tools (e.g., Snakemake, Nextflow) and version control systems (e.g., Git).
• Hands-on experience with AI and machine learning frameworks (e.g., PyTorch, TensorFlow, Scikit-learn) and their application in bioinformatics.
• Expertise in bioinformatics tools and databases for genomics, metagenomics, and other omics fields (e.g., MetaPhlAn, CARD, NCBI, UniProt, etc.).
• Strong knowledge of statistical methods and computational frameworks for multi-omics data integration.
• Data Management: Proven experience in designing and maintaining robust data management systems to ensure data quality, reproducibility, and readiness for downstream analyses.
• Familiarity with cloud-based storage solutions and high-performance computing environments is a plus.
• Omics Expertise: Experience in analyzing and integrating multi-omics datasets, including genomics, transcriptomics, proteomics, and metabolomics.
• Ability to interpret complex datasets and translate them into actionable insights.
• Automation Skills: Experience in developing computational workflows to automate experimental data analysis for flow cytometry, microscopy, and other molecular biology results is highly desirable.
• Ability to support scientists in maximizing the value of experimental data through high-throughput and reproducible analyses.
• Soft Skills: Strong communication and presentation skills, with the ability to effectively convey complex concepts to both technical and non-technical audiences.
• Excellent interpersonal and collaboration skills, with the ability to work effectively in a global, multidisciplinary team.
• Adaptability: A proactive and innovative mindset, with the ability to thrive in a fast-paced and dynamic research environment.
• Strong problem-solving skills and the ability to manage multiple projects simultaneously.

• Challenging tasks, short decision-making processes and a high level of personal responsibility in a modern work environment with flexible work time models
• Room for innovative thinking and growth with the possibility to manage your own career path.
• A company culture which promotes continuous learning, diversity and inclusion.
• Excellent career opportunities in a world leading nutrition company.
• An attractive remuneration including a variety of social benefits like subsidized health & fitness offers.

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