The Chair of Epidemiology at the Medical Faculty of the University of Augsburg at Augsburg University Hospital is seeking to fill a part-time position (50% of the regular working hours) for a Data Scientist (m/f/d) or Bioinformatician (m/f/d), for a duration of two years, starting as soon as possible.

Your Responsibilities

• Independently identify, develop, and implement computational and statistical methods for analyzing -omics data
• Apply machine learning approaches to explore and model the relationship between dietary factors and gut microbiota composition/function
• Collaborate with interdisciplinary teams to design analyses and interpret findings
• Contribute to scientific publications and reports

Your Qualifications

• Doctorate or master’s degree and relevant experience in Data Science, Bioinformatics, Statistics, Computational Biology, or a related field
• Strong background in machine learning, statistical modeling, and data visualization
• Experience in analyzing -omics datasets is desirable
• Proficiency in programming languages including R and/or Python
• Ability to work independently and as part of a multidisciplinary team
• Excellent written and verbal communication skills
• Proficiency in English or German at the C1 level is essential

Our Offer

• We offer you an interesting and responsible position in an interdisciplinary team, along with good opportunities for further training and development
• Your workplace is located on the campus of the Augsburg University Hospital and is easily accessible by public transport. Hybrid remote work is an option
• The initial employment is for a limited period of two years
• Compensation according to the collective agreement (TV-L), depending on qualifications and professional experience, including public sector social benefits (company pension scheme, annual special payment)
• Attractive offers as part of corporate health management, such as yoga classes, fitness programs, and much more
• Employee discounts with various companies

Contact

• Independently identify, develop, and implement computational and statistical methods for analyzing -omics data
• Apply machine learning approaches to explore and model the relationship between dietary factors and gut microbiota composition/function
• Collaborate with interdisciplinary teams to design analyses and interpret findings
• Contribute to scientific publications and report