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Stellenangebote

1 postdoc and 1 senior scientific software developer

we have 2 open positions: 1 postdoc and 1 senior scientific software developer.

You will embark on our newly funded ERC Synergy consortium EPIC, to design and train AI models from multimodal data for 100 species across all layers of gene expression. Unravel complex regulatory instructions, their evolution, and design genes with intended regulation.

Job ads: https://tinyurl.com/cmm-jobs 

About EPIC: https://tinyurl.com/epic-news-tum  

Prof. Julien Gagneur
Chair of Computational Molecular Medicine
School of Computation, Information and Technology (CIT)
Technical University of Munich

PhD Student Position, Structural Bioinformatics

The Bioinformatics group of the Max Planck Institute of Molecular Plant Physiology, Potsdam-Golm) is looking to fill a Phd student position to work on projects associated with structural bioinformatics and machine learning. The ideal candidate will have a formal training in Bioinformatics (or related discipline), in particular in structural bioinformatics and state-of-the-art machine learning, should have strong programming skills, should feel passionate about science, be self-motivated and genuinely curious.

To apply, please send your CV including the contact information of two references to Prof. Dirk Walther (Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!)

https://www.mpimp-golm.mpg.de/bioinformatics, https://www.mpimp-golm.mpg.de/2168/en 

PhD student in Bioinformatics for Rare Disease Research

Are you passionate about the application of bioinformatics to genome-based medicine? The Chair of Computational Molecular Medicine at the Technical University of Munich (TUM) is seeking a talented and driven individual to join our dynamic team. As part of the newly funded European project ERDERA, you will develop innovative bioinformatics methods to improve and accelerate diagnostics and identification of treatment options for rare diseases.

About us
The Chair of Computational Molecular Medicine, led by Prof Julien Gagneur, develops computational approaches to study genomes. Applications of our work range from understanding basic mechanisms governing gene expression to unravelling genetic aberrations triggering rare diseases and cancer. More at https://www.cs.cit.tum.de/cmm/home/.

The project
ERDERA, the European Rare Disease Research Alliance (https://www.ejprarediseases.org/erdera/) is a new 7-year EC-funded project starting 1st September 2024. ERDERA aims to improve the diagnosis and treatment of rare diseases in Europe. It integrates under one roof research capacity, resources, and service from 171 public institutions, hospitals, and companies spanning patient recruitments, genome sequencing and omics profiling, data integration, software development for diagnosis and treatment recommendations, and the development of new therapeutics. ERDERA collaborates with national initiatives such as Germany’s genomic medicine project (https://www.bundesgesundheitsministerium.de/en/en/international/european-health-policy/genomde-en.html) that will yield 10,000s of genomes from routine diagnostics for research. Our team co-leads the ERDERA work package on “Diagnostic Research Workstream - Genomic innovation to shorten time to diagnosis”.

Your role
You will develop and apply methods that jointly process DNA variants and results derived from RNA-seq data to increase analysis speed and reliability. This will include improving and integrating non-coding variant annotation tools and aberrant event callers, for which our lab has made substantial contributions (e.g. AbSplice, AbExp, OUTRIDER, FRASER). You will integrate data from multiple centers, develop and implement workflows covering quality control procedures, comprehensive analysis, and automatically generated reports. Moreover, you will develop guidelines for results interpretation and follow-up on their implementation and outcome.

More information:
 https://drive.google.com/file/d/1wQirTZABk6liyd-MIoZb_wMrAbkro0Pz/view

  

Postdoc in Bioinformatics for Rare Disease Research

We are currently looking for a full-time Postdoc in Bioinformatics for Rare Disease Research. Are you passionate about the application of bioinformatics to genome-based medicine? The Chair of Computational Molecular Medicine at the Technical University of Munich (TUM) is seeking a talented and driven individual to join our dynamic team. As part of the newly funded European project ERDERA, you will develop innovative bioinformatics methods to improve and accelerate diagnostics and identification of treatment options for rare diseases.

About us
The Chair of Computational Molecular Medicine, led by Prof Julien Gagneur, develops computational approaches to study genomes. Applications of our work range from understanding basic mechanisms governing gene expression to unravelling genetic aberrations triggering rare diseases and cancer. More at https://www.cs.cit.tum.de/cmm/home/.

The project
ERDERA, the European Rare Disease Research Alliance (https://www.ejprarediseases.org/erdera/) is a new 7-year EC-funded project starting 1st of September 2024. ERDERA aims to improve the diagnosis and treatment of rare diseases in Europe. It integrates under one roof research capacity, resources, and service from 171 public institutions, hospitals, and companies spanning patient recruitments, genome sequencing and omics profiling, data integration, software development for diagnosis and treatment recommendations, and the development of new therapeutics. ERDERA collaborates with national initiatives such as Germany’s genomic medicine project (https://www.bundesgesundheitsministerium.de/en/en/international/european-health-policy/genomde-en.html) that will yield 10,000s of genomes from routine diagnostics for research.
Our team co-leads the ERDERA work package on “Diagnostic Research Workstream - Genomic innovation to shorten time to diagnosis”.

Your role
You will develop and apply methods that jointly process DNA variants and results derived from RNA-seq data to increase analysis speed and reliability. This will include improving and integrating non-coding variant annotation tools and aberrant event callers, for which our lab has made substantial contributions (e.g. AbSplice, AbExp, OUTRIDER, FRASER). You will integrate data from multiple centers, and develop and implement workflows covering quality control procedures, comprehensive analysis, and automatically generated reports. Moreover, you will develop guidelines for results interpretation and follow-up on their implementation and outcome. Also, you will be involved in the scientific coordination of workshops and data analysis hackathons.

More information:
 https://drive.google.com/file/d/1UWraqsqW9Q8YStKNW3bxDQIFr0xeyeTu/view

 

 

Postdoctoral Research Fellow (f/m/d)

Boehringer Ingelheim AI & Data Science Fellowship Program

The AI & Data Science Fellowship Program, a cooperation between the University of Tübingen, distinguished as excellent by the Federal Government of Germany, and Boehringer Ingelheim, a leading pharmaceutical company, is inviting applications for a

Postdoctoral Research Fellow – AI & Data Science (f/m/d; E13 TV-L, 100%)

to work on cutting-edge and exciting AI & data science research topics that generate real added value for human and animal healthcare.

https://uni-tuebingen.de/en/university/careers/newsfullview-job-advertisements/article/postdoctoral-research-fellow-f-m-d-e13-tv-l-100/ 

Single-Cell RNA-Seq Data Analysis: A Practical Introduction in Berlin

Master the tools and techniques to confidently analyze single-cell RNA-seq data and gain new insights into complex biological systems

In a nutshell

 

  • Explore sequencing technologies for single-cell analysis
  • Process QC and analyze single-cell RNA-seq data
  • Learn how to identify and annotate cell clusters
  • Discover how to integrate and analyze multi-sample data

The Single-Cell RNA-Seq Workshop is designed to provide a thorough introduction to the analysis of single-cell RNA sequencing data. Through a combination of lectures and hands-on exercises, participants will learn how to process, analyze and integrate single-cell data using industry-standard tools and techniques. Topics covered include sequencing technologies, data quality control, preprocessing, dimensional reduction, clustering, trajectory inference, differential expression analysis, and multi-sample integration.

By the end of the workshop, attendees will have the skills and confidence to perform custom analyses and gain new insights into complex biological systems. This workshop is ideal for researchers and students with little or no prior experience in single-cell RNA-seq analysis, as well as those seeking to update their skills and knowledge.

 


Links: https://www.ecseq.com/workshops/workshop_2023-07-Single-Cell-RNA-Seq-Data-Analysis

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