Fachbereich Biologie, Chemie, Pharmazie - Institut für Biologie AG Hiesinger

Freie Universität Berlin; Berlin; Vor Ort; EUR 40.000 - 60.000; Vollzeit

Zusammenfassung

A leading research university in Berlin is seeking an information theorist with a PhD in mathematics or a related field. The role involves analyzing connectome data from fly brains and developing models to measure the information capacity of neural wiring. Candidates should have experience in information theory and be prepared to collaborate closely with experimental scientists. This unique position integrates theoretical and practical research within a dynamic academic environment.

Qualifikationen

• University-level education in mathematics or bioinformatics.
• Experience in theoretical development of information theory models.
• Strong background in analyzing biological neural networks.

Aufgaben

• Analyze connectome data of synaptic connections in fly brains.
• Develop models to measure information capacity of brain wiring.
• Collaborate with experimental scientists on data interpretation.

Kenntnisse

Information theory

Mathematical modeling

Bioinformatics

Ausbildung

PhD in mathematics or a related field

Jobbeschreibung

The Hiesinger lab is a basic research neurobiology lab at the Free University in Berlin Germany. The main focus of the lab is the study of how genomic information 'unfolds' to develop neural networks with remarkable information content: flies, which we use as a model, have brains that compute flying in 3D, navigation, metabolism and advanced learning and memory capabilities - all prior to any training. Our team includes neuroscientists, advanced laser microscopists (to live observe brain wiring), bioinformaticians and closely collaborating mathematicians.

Starting in we are conducting a dedicated study entitled 'The Information content of brain wiring', funded by the Volkswagen Foundation Pioneering Research Program 'the unknown unknown.' The basic premise is simple: The information content of artificial neuronal networks can be saved in precise bits, yet no such number has ever made sense for biological neuronal networks. Not only the number, even what parameters should be quantified remains unclear – a true unknown unknown to be tackled experimentally within an information theoretical framework.

The laboratory is part of a larger university community and an interdisciplinary research consortium to study brain wiring that includes.

Job description

We are seeking an information theorist with an academic background in mathematics or bioinformatics and a specialization in information theory (Shannon entropy, compressibility, effective complexity and logical depth). The data basis for the analyses are two-fold: first, recent connectome data, i.e. large datasets of all synaptic connections in the fly brain based on electron‑microscopic reconstruction; second, high‑resolution live imaging data of the developmental transformations that encode information in biological neural networks. The information theorist will be embedded with experimental scientists and other mathematicians to develop the tools to analyse this data and come up with a measure of both information capacity and information content of brain wiring.

Requirements

PhD in mathematics or a related field.

Professional Experience

Previous academic experience with information theory in basic or applied research. We are not looking for a data analyst of 'omics' data, but a theorist with the expertise to develop new ideas and models.