Internship on establishing in-house pipelines to support spatial-omics data analysis (9 months, Basel)

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The Position

Project Description:
 

Recent advancements in High-Plex Spatial Proteomics (HPSP) technologies have significantly enhanced our understanding of protein expression within the complex spatial architecture of tissues. Building upon recent developments in bioinformatics and data analysis, the proposed project seeks to establish robust, in-house computational pipelines for the analysis of HPSP data. These pipelines will integrate a range of analytical techniques, including image processing, spatial statistics, and machine learning, to extract meaningful biological insights from complex datasets. The goal is to develop standardized workflows that can efficiently process and analyse HPSP data, from raw image acquisition to the interpretation of protein expression patterns across diverse tissue types.

The project will be carried out in close collaboration with the Jiang Lab (https://sizunjianglab.com/), leveraging their expertise in both spatial proteomics and computational biology. The ideal outcome of the project would be a scientific publication detailing the quantitative analysis using the developed pipeline of some of our internal datasets. We are seeking candidates who are passionate about computational biology and data analysis, with a strong background in bioinformatics, machine learning, and a keen interest in spatial-omics technologies. For exceptional candidates, this position may offer the potential for further research opportunities, such as pursuing a PhD program within the lab.

The position is based in Basel within the Pharmaceutical Sciences department, providing a dynamic environment at the intersection of cutting-edge research and clinical applications. We anticipate close collaboration with various groups, including experts in bioinformatics, pathology, and advanced genomics tools, ensuring a multidisciplinary approach to the project. Additionally, as highlighted above, we envision a strong partnership with our academic collaborators at the Jiang Lab, leveraging their specialized expertise in spatial proteomics and computational analysis to drive innovation in our projects

Project mission:

• Establish a robust pipeline to routinely analyse High-Plex Spatial Proteomics Data 

• Utilize the developed pipeline to analyse some of our internal datasets.

• Scientific publication

Your impact and main responsibilities:

This internship aims to develop a robust pipeline that enables routinely and standardize analysis of High-Plex Spatial Proteomics Data. We aim to use the pipeline in a very interesting internal dataset that can lead to a scientific publication. As an intern, you will receive the guidance and support needed to conduct independent research, and you will be encouraged to approach the problem creatively. Your main responsibilities will be conducting a literature review, interacting with our academic collaborators, implementing the required functions for the data analysis and critically evaluating obtained results.

Who You are:

• A Bachelor's and a Master's degree in a relevant field (e.g., Computer Science Bioinformatics, Biotechnology etc.).

• Strong coding skills in Python/R, and familiarity with Git, Docker, and other best practices

• Experience with high performance computing and bash/unix

• Proficiency in English (written, spoken).

• Experience in computational biology or bioinformatics and omics data analysis.

• Interest in Spatial Biology approaches in e.g. Immunology, or Neuroscience  

• Being familiar with different Machine Learning techniques
   

Your application:

Please upload your CV, with at least two references, and a cover letter. Both documents are mandatory. Optionally, you can include at least one software repository of your previous work in your CV.

Due to regulations, non-EU/EFTA citizens have to provide a certificate from the university stating that an internship is mandatory and the length of the mandatory internship as part of the application documents.

Additional Information:

Duration of Internship: 9 months
Estimated Starting Date: March 2025 
Location: Basel, Switzerland

Do you feel excited? Apply now!

Who we are

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