Jeden Tag für das Leben

Stellenbeschreibung
Welches AiM Formular soll verwendet werden?:  DE_Standard
Kennziffer:  887
Befristet / Unbefristet:  Befristet
Zeitmodell Vollzeit / Teilzeit:  Vollzeit
Entgeltgruppe:  E13
Geplanter Einstellungstermin:  as soon as possible
Fachabteilung:  Peter L. Reichertz Institut für Medizinische Informatik
Peter L. Reichertz Institut für Medizinische Informatik
Research Associate (f/m/d) (PhD Candidate)

About Us

The Peter L. Reichertz Institute for Medical Informatics (PLRI) at Technische Universität Braunschweig and Hannover Medical School (MHH) is offering a position as a Research Associate (m/f/d) with the opportunity to pursue a PhD within the junior research group Computational Precision Nutrition.
 
PLRI is one of the largest academic centers for medical informatics in Germany and is jointly operated by two leading universities in one of Europe’s most research-intensive regions. It provides an excellent environment for interdisciplinary research at the interface of data science, medicine, and healthcare.
 
The newly established research group Computational Precision Nutrition investigates how individual responses to diet can be better understood and predicted using multi-omics data (particularly microbiome and metabolome) and data-driven approaches. The goal is to develop personalized nutrition strategies while ensuring biological interpretability of models.
 
PLRI collaborates closely with clinical partners, research institutes, and national and international networks. Activities range from local collaborations in Hannover and Braunschweig to large-scale European research projects.

What We Offer

  • Structured PhD training with close supervision in a newly established research group
  • Opportunity to work on a highly relevant, interdisciplinary research topic
  • lose collaboration with clinical partners and international research networks
  • A 6-month research stay at the Institute of Systems Biology, Maastricht University
  • Opportunities for methodological development in machine learning and artificial intelligence
  • Flexible working hours and a high degree of scientific independence
  • Attractive public sector employment conditions (including pension scheme and additional benefits) with one of the largest employers in Lower Saxony
  • Comprehensive benefits including structured onboarding, training opportunities, health programs, good transport connections, and bike leasing options

Your Responsibilities

  • Analysis and integration of multi-omics data (in particular microbiome, metabolome, and dietary data) from intervention studies and cohort studies
  • Development, implementation, and evaluation of statistical models and machine learning approaches to predict individual dietary responses
  • Application and further development of methods for integrating heterogeneous data types (e.g., network analysis, probabilistic models, causal inference approaches)
  • Development of reproducible analysis pipelines in R and/or Python
  • Preparation of scientific publications and presentation of results at international conferences
  • Close collaboration with clinical partners, bioinformaticians, and nutrition scientists
  • Contribution to the development of research questions and project ideas within the group

Your Profile

  • Master’s degree (or equivalent) in bioinformatics, data science, statistics, nutrition science, or a related field
  • Strong interest in interdisciplinary research at the intersection of nutrition, microbiome research, and data science
  • Solid knowledge of statistical data analysis (e.g., regression models, multivariate methods, machine learning) and strong programming skills in R and/or Python
  • Ideally, experience in analyzing high-dimensional data (e.g., omics data)
  • High motivation to pursue a PhD and ability to work independently
  • Team spirit, openness, scientific curiosity, and strong communication and learning skills
  • Excellent English skills (written and spoken)

Application Documents

Please submit the following documents:
  • Motivation letter
  • Curriculum vitae (CV)
  • Academic transcripts and certificates (Bachelor’s and Master’s, including transcript of records)
  • Master’s thesis (or equivalent scientific work) or, alternatively, a short abstract of the thesis (max. 1 page)

Deine Ansprechperson

Mattea Müller
+49 (0)511 532 30880
Bewerbungsschluss:  10.05.26

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Die MHH ist zertifizierte familiengerechte Hochschule und setzt sich für die Förderung von Frauen im Berufsleben ein. Bewerbungen von Frauen sind besonders erwünscht. Schwerbehinderte Bewerber:innen werden bei gleicher Qualifiaktion bevorzugt berücksichtigt.

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