The Center for Humans and Machines, Max Planck Institute for Human Development, is seeking applications for a

Postdoctoral Research Position

(E 13 TVöD; 39 hours/week)

Funding for the postdoctoral position is available for two years, with possibility of extension for a third year. The position is available from February 1, 2020, or later. Job description
The successful candidate will work under the direct supervision of Dr. Cebrian (Machine culture group) and Dr. Pescetelli (Hybrid collective intelligence group). Long-term supervision and strategic advice will be provided by the Center's director Dr. Rahwan. The project aims to quantify the impact of digital technologies on human social learning. The post-doctoral researcher will need to analyse large datasets collected online to discern macroscopic patterns in human behavior, using computational and data mining skills. The successful candidate will have no formal teaching requirements. The project is part of the Center for Humans and Machines (director: Iyad Rahwan) at the Max Planck Institute for Human Development (MPIB) in Berlin. The successful candidate will work in a multidisciplinary team with a clear scientific question, to produce high impact publications in top journals. Requirements
We are searching for a postdoc with a strong interest and established expertise in data science and pattern recognition. The successful applicant must be comfortable working with large multidimensional datasets and complex statistical models. The position is open to candidates holding a doctoral degree in either physics, computer science or in a related field. Essential
The successful applicant needs to possess:

• Outstanding experience in data science and/or pattern recognition, as demonstrated by a track record of publications in top scientific journals or conferences.
• Expertise with data mining skill set, including (but not limited to) feature extraction, clustering, dimensionality reduction, and statistical modeling
• Experience working with parallel computing and large amounts of data
• Ability to apply information theory to practical problems
• Ability to draw causal conclusions from observational data
• Ability to work independently and creatively
• Willingness to work in a multidisciplinary and fast-paced environment
• High proficiency in English

Preferable
Proficiency also in one (or more) of the following skills will be advantageous to the successful applicant:

• Experience in Bayesian statistics and Bayesian networks
• Experience in path analysis and mediation
• Experience in phylogenetic models
• Experience in machine learning and reinforcement learning

The Max Planck Society strives for gender and diversity equality. We welcome applications from all backgrounds. The Max Planck Society is committed to increasing the number of individuals with disabilities in its workforce and therefore encourages applications from such qualified individuals.