Boehringer Ingelheim
09 March 2016

BIGCHEM – Big Data in Chemistry

As a pharmaceutical company with a 130-year history, we know full well what a difference it makes when you have good connections with one another: it creates an informal environment combined with just the right amount of innovative energy. That’s why we offer students and graduates with a background in mathematics, science, technology, or IT the opportunity to get involved in plenty of exciting projects where they can really show off their talents. Therefore Boehringer Ingelheim is now partner of BIGCHEM.

Section title

Substantial challenges for computational analysis arise from size, complexity and heterogeneity of available data sets.

Life sciences data is generated and published at unprecedented rates. This wealth of data provides unique opportunities to generate new insights into the mechanisms of disease and to identify starting points for treatments. Substantial challenges for computational analysis arise from size, complexity and heterogeneity of available data sets.

A further major challenge facing biomedical research today is the handling and analysis of this very large amounts of data that the researchers themselves are generating. This topic is referred to as 'Big Data' and in the future, the project BIGCHEM (Big Data in Chemistry) will deal with this topic.


BIGCHEM is a Marie Skodowska-Curie Innovative Training Network (ITN) for Early Stage Researchers (ESR) and evaluates the chemical properties and biological activities of very large chemical compound libraries that are, for example, the basis for high throughput screening approaches in pharmaceutical drug discovery.


The research program of BIGCHEM aims to develop innovative analysis solutions for big (bio)chemical data and will provide unique education and research opportunities for 10 doctoral students at the interface of academia and industry with a comprehensive and cross-disciplinary curriculum in (bio)chemical data analysis, including machine-learning, computational chemistry and chemoinformatics methods.


Selected applicants will be given the opportunity to work on a three-year PhD project in two friendly, open-minded, multidisciplinary environments with high emphasis on exciting science and team work. Each doctoral student will spend at least 50% of the time with industrial partners. Nine renowned participants from science and industry and eight additional partner organizations are cooperating in BIGCHEM across Europe.

Boehringer Ingelheim is involved in the following four ESR projects:


ESR1: Machine learning methodologies for mining very large compound data sets.

(Boehringer Ingelheim Pharma GmbH & Co KG and University of Bonn, Germany)


ESR2: Computational compound screening and profiling by large-scale mining of pharmaceutical data

(Boehringer Ingelheim Pharma GmbH & Co KG and University of Bonn, Germany)


ESR3: Big data visualisation and modelling using Generative Topographic Mapping

(University of Strasbourg and Boehringer Ingelheim Pharma GmbH & Co KG, France & Germany)


ESR7: Exploration of uncharted regions of the chemical space by reaction-driven de novo design

(Boehringer Ingelheim Pharma GmbH & Co KG and ETH Zürich, Germany & Switzerland)


Further information about these projects, the other ESR projects, the recruitment process as well as the eligibility criteria can be found on the BIGCHEM site Applications should be submitted online through the project website. Deadline for applications is 20.03.2016.

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