1 Postdoc (m/f/d) in Causal Inference / Statistics

Arbeitsagentur; Bergholz-Rehbrücke; Vor Ort; EUR 60.000 - 76.000; Vollzeit

Benefits dieser Stelle

30 days vacation

Corporate Benefits program

Jobticket for public transport

Zusammenfassung

The German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE) invites applications for a Postdoc (m/f/d) in Causal Inference / Statistics. Starting as soon as possible, the successful candidate will join the Department of Computational Precision Nutrition to develop causal inference methods for individual-level analyses and multimodal data, in collaboration with clinicians and data scientists.

Responsibilities include applying causal models to health interventions, contributing to N-of-1

Qualifikationen

• Excellent master and doctoral degree with demonstrated expertise and publications in Causal Inference and Statistics.
• Expertise in programming languages such as R or Python.
• Experience with open-source software development.
• Strong communication skills and ability to work in interdisciplinary teams.

Aufgaben

• Develop and apply methodology for individual-level inference on the effect of health interventions
• Develop best practices and guidelines for causal inference in N-of-1 trials
• Develop and apply methodology to investigate treatment effect heterogeneity
• Collaborate with deep learning researchers to jointly develop methods for analyzing multimodal digital N-of-1 trials (patient reported outcomes, wearables, images, audio, omics data) linking causal inference and deep learning
• Implement the developed causal inference methodology for studies run on the StudyU platform with collaborators in Germany, Australia, USA, South Korea and Ghana
• Develop clear data visualizations, reports, and written summaries to communicate results – for scientific publications but also for study participants and patients
• Collaborate with clinicians, epidemiologists, software developers and laboratory scientists in the design of new studies and analysis of existing data

Kenntnisse

Causal Inference

Statistics

R

Python

Open-source software

Communication

Ausbildung

Master and PhD in Statistics/Mathematics/Computational Science

Jobbeschreibung

The German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE) is a member of the Leibniz Association. The institute’s mission is to conduct experimental and clinical research in the field of nutrition and health, with the aim of understanding the molecular basis of nutrition-dependent diseases, and of developing new strategies for treatment and prevention.

1 Postdoc (m/f/d) in Causal Inference / Statistics

starting as soon as possible.

The Department of Computational Precision Nutrition develops methods and software for the analysis of both population-level and individual-level data, to enable personalized health recommendations based on dietary patterns, behaviors, and diet-associated biomarkers. We aim to contribute to the personalized prevention and treatment of chronic diseases and advance our understanding of the mechanisms underlying their development. Two methodological focus areas are digital N-of-1 trials and deep learning-based modeling of multimodal biomedical data.

We are seeking one highly motivated scientist with expertise in Causal Inference and Statistics to join our team.

Tasks

• Develop and apply methodology for individual-level inference on the effect of health interventions
• Develop best practices and guidelines for causal inference in N-of-1 trials
• Develop and apply methodology to investigate treatment effect heterogeneity
• Collaborate with deep learning researchers to jointly develop methods for analyzing multimodal digital N-of-1 trials (patient reported outcomes, wearables, images, audio, omics data) linking causal inference and deep learning
• Implement the developed causal inference methodology for studies run on the StudyU platform with collaborators in Germany, Australia, USA, South Korea and Ghana
• Develop clear data visualizations, reports, and written summaries to communicate results – for scientific publications but also for study participants and patients
• Collaborate with clinicians, epidemiologists, software developers and laboratory scientists in the design of new studies and analysis of existing data

Skills and requirements

• Excellent master and doctoral degree with demonstrated expertise and publications in Causal Inference and Statistics
• Expertise in programming languages such as R or Python
• Experience with open-source software development
• Strong communication skills and ability to work in interdisciplinary teams

We offer

• Opportunity to develop your own research profile within an exciting research area
• A dynamic, international and interdisciplinary research environment as well as excellent working conditions and outstanding technical equipment
• Employment with remuneration according to TV-L, level 13, plus annual special payment and company pension scheme
• Family-friendly working conditions (certificate “audit berufundfamilie”)
• Supporting of mobility with a jobticket for using the public transport
• Location close to the vibrant city of Berlin, with easy accessibility by public transport or car
• 30 days of vacation
• Participation in the benefits program for employees („Corporate Benefits“)

The advertised position is available for initially 3 years.

We promote the employment of people with severe disabilities and are committed to equal opportunities for them. Applicants with severe disabilities will be given preferential consideration if they have the same qualifications.

We look forward to your application!

For further information please contact

Prof. Dr. Stefan Konigorski

Head of the Department of Computational Precision Nutrition

E-Mail: [e-mail]

We process your application documents for the purpose of carrying out the application procedure in accordance with Art. 6 para. 1 lit. b) GDPR, Art. 88 GDPR. For more information on the collection, processing and use of personal data by the German Institute of Human Nutrition as part of the application process and your rights under data protection law, please contact the Department of Human Resources and Social Services ([e-mail]).