The Zuse Institute Berlin (ZIB) is a non-university research institute under public law of the state of Berlin.

The division Mathematics for Life and Materials Sciences is offering within the newly formed Berlin Big Data Center (BBDC) a Research position (f/m) „Analysis of very large biomedical data sets“

Pay grade E 13 TV-L Berlin (100%)
Reference code: WA 11/15

The position will be a fixed-term contract for two years with the option to be extended. 

Tasks

Perform algorithmic, application-oriented research in the project "Analysis of very large biomedical data-sets”, specializing on machine learning for big data, with particular focus on scalable, parallel/distributed algorithms.

We expect

• participation in the research program of BBDC
• publication activity in leading scientific journals and conferences
• collaboration with industrial partners
• participation in acquisition of third-party funds
• co-supervision of Bachelor and Master theses  

The successful candidate will work in an inspiring and pleasant environment and will receive adequate professional support. We offer a challenging scientific task, a high degree of autonomy and state-of-the-art technical infrastructure. Non-PhD candidates are strongly encouraged to pursue a doctoral degree in conjunction with this work.

Since ZIB is an equal opportunities employer, we kindly encourage female candidates to apply for this job offer.

Persons with disabilities will be given preference, when equally qualified.

To submit your application, please click on the "APPLY" button. Please send your application, quoting the reference code WA 11/15, including CV and all relevant documents.

For more information about the field of work, please visit www.zib.de or contact the project head Prof. Christof Schütte (schuette@zib.de). Please note: applications directed to this email will not be considered.

Requirements

• master or diploma in computer science, mathematics, bioinformatics or related discipline
• good knowledge and experience in data analysis, both theory and method development, specifically in one or more of the following areas: Bayesian estimation, statistical learning, reinforcement learning, and distributed statistics with collaborative computing
• knowledge and experience in bioinformatics or in image analysis
• very good Java or C++ programming skills
• very good communication skills in English

Additional preferred skills

• knowledge of machine-learning techniques for handling “Big/Complex Data”, e.g. design of scalable algorithms running on parallel and cloud architectures, knowledge in graph-mining or large-scale programming (for instance Hadoop MapReduce)
• experience regarding Big Data applications, e.g. distributed data analysis, recommender systems, collaborative filtering, social networks analysis, computational advertising, or behavioral targeting