Postdoctoral Position in the Computational Neurobiology Lab

VIB; Antwerpen; On-site; EUR 40,000 - 60,000; Full time

Job summary

VIB in Antwerp, Belgium invites applications for a Postdoctoral Position in the Computational Neurobiology Lab. The project investigates regulatory mechanisms of isoform switching in dementia, leveraging genome-wide profiling and multimodal data integration to map chromatin and regulatory networks in brain health and disease.

The ideal candidate has a PhD in computational biology or related fields, strong computational skills (R/Python), and proven experience with single-cell analyses, 3D

Qualifications

• PhD in computational biology, systems biology, bioinformatics or related field.
• Strong computational experience and track record in research.
• Experience with single-cell data and multimodal data integration.
• Experience reconstructing gene regulatory mechanisms and 3D chromatin concepts.
• Fluent English with excellent writing and communication skills.

Responsibilities

• Perform advanced computational analyses on isoform regulation in brain diseases.
• Develop regulatory atlases and identify causal elements in dementia contexts.
• Integrate multi-omics data to study ATSS/ATTS mechanisms.
• Collaborate with wet-lab and clinical teams to validate findings when possible.

Skills

Single-cell analysis

Multimodal data integration

Gene regulatory networks

3D chromatin analysis

R and Python

English communication

Strong academic record

Education

PhD in computational biology or related

Job description

Postdoctoral Position in the Computational Neurobiology Lab

VIB
Antwerp, Belgium

Project description

In the Computational Neurobiology lab, we study causal mechanisms underlying normal and aberrant cellular decision-making in the human brain in health and neurodegenerative diseases. More specifically, we investigate the role of spatial chromatin organization in cell fate acquisition and maintenance, using a variety of targeted and genome-wide profiling technologies and develop statistical and machine learning approaches for multimodal data integration and cis-regulatory network reconstruction.

We are looking for a talented and highly motivated postdoctoral scientist to work on a project at the intersection of genetics, systems biology and computational biology to study the regulatory mechanisms underlying cell-type specific switching of alternative gene isoform in different types of dementia, generously supported by the Alzheimer's Association.

The human brain shows some of the widest isoform diversity of any organ and has therefore been an important model for studying alternative splicing. Intriguingly, recent data showed widespread changes in isoform usage, specifically in usage of alternative transcription start site (ATSS) and alternative transcription termination site (ATTS) of causal disease genes, in Alzheimer's disease (AD), Parkinson's disease (PD) and Dementia with Lewy Bodies (DLB). This brings to the forefront the significance of ATTS/ATTS choice across neurodegenerative diseases and the need for comprehensive holistic research into the mechanisms regulating it, as currently the knowledge of these mechanisms is severely lacking. Most recently, large-scale changes in 3D chromatin organization and epigenetic factors have been shown to affect or correlate with alternative splicing/exon usage. Yet, a systematic study of the precise mechanisms governing ATSS/ATTS choice, on a genome-wide scale at high-resolution, and of the role of the combined action of chromatin organization and epigenetic factors in these mechanisms has not been conducted until now. The proposed project is aiming to bridge this gap via (i) building isoform-specific regulatory atlas for the human brain in health and disease, (ii) identifying causal regulatory elements and transcription factors responsible for determining ATSS and ATTS choice in disease and (iii) identifying putative causal disease isoforms with a genetic underpinning in dementia.

Your profile

• Either a fully computational background (PhD in computational biology, systems biology, bioinformatics or related disciplines), or a hybrid background with a strong computational experience (PhD in molecular biology, biomedical sciences, functional genomics or related disciplines)
• solid knowledge of and experience in single-cell data analysis and multimodal data integration
• solid knowledge of and experience in reconstruction and analysis gene regulatory mechanisms
• solid knowledge of 3D chromatin organisation principles
• intermediate/advanced programming skills in R and/or Python
• excellent communication and writing skills in English
• strong academic record

Additional beneficial skills

• experience with analysis of 3D chromatin organization data
• experience with analysis of proteomics data