Postdoctoral Researcher / Postdoctoral Researcheress

Postdoctoral Position in Development and Application of Computational Methods for Functional Genomics

100%, Basel, fixed-term

The Laboratory for Biological Engineering (Prof. Randall J Platt) at ETH Zurich in Basel, Switzerland, is dedicated to developing genome engineering technologies applied to a variety of fundamental and disease-focused research areas. To further these efforts, the Platt group is seeking a full-time (100%) Postdoctoral Associate to develop and apply computational methods for novel experimental functional genomics datasets.

Project Background

Our lab builds high-throughput experimental platforms that necessitate the creation of equally innovative computational methods. The candidate will contribute to two key areas:

• In vivo Single-Cell CRISPR Perturbation Screens
  CRISPR perturbation screens, such as Perturb-seq, are transforming our approach to studying gene function at scale. We have recently pioneered an AAV-based method for direct in vivo single-cell CRISPR screening (Santinha, Nature, 2023) and are expanding our efforts to create in vivo cell-type perturbation atlases, investigate disease mechanisms, and identify therapeutic targets. These initiatives will yield extensive, rich perturbation datasets, necessitating the development of sophisticated methods, incorporating machine learning and modeling techniques.
• Transcriptome Recording and Cellular History Reconstruction
  We are advancing our CRISPR-based transcriptional recording method (Schmidt, Nature, 2018; Tanna, Nature Protocols, 2020) that encodes transient cellular events into DNA for sequencing readout. The computational challenges include the detection of biological signals while applying Record-seq to complex in vivo environments (Schmidt, Science, 2022), especially within the context of drug-host microbiome interactions, alongside the development of dedicated tools for the novel data modality produced by Record-seq.

Job Description

We are seeking a highly motivated and collaborative researcher to join our team. The candidate will be part of a multidisciplinary team and should possess a passion for science, technology, collaboration, and communication. The role includes closely collaborating with laboratory members (both experimental and computational) and engaging in planning projects and experiments, developing computational methods, analyzing and integrating omics datasets, and interpreting findings.

Key Responsibilities

The candidate will primarily engage in the following activities:

• Develop analysis methods and provide guidance on experimental design (e.g., target gene selection, power analyses, guide-library design, readout selection).
• Build, maintain, and document reproducible analysis pipelines (Python/R; Snakemake/Nextflow preferred) for novel experimental methods.
• Develop and apply methods for demultiplexing, normalization/QC, effect-size estimation, biological inference, and predictive modeling.
• Contribute to biological manuscripts and methods papers, present results within the lab and at conferences, and assist in mentoring students.
• Utilize and maintain lab resources on HPC and GitHub. Daily tools will include Python and R, version control (Git), and HPC schedulers.

Candidate Profile

The ideal candidate will possess at least a PhD or equivalent in Bioinformatics, Computational Biology, Computer Science, Applied Statistics, or a related field. Effective communication in a highly interdisciplinary and international setting, particularly proficiency in oral and written English, is essential.

Required Skills and Experience

Extensive prior experience in the following areas is essential:

• Strong Python and R skills; solid software-engineering practices (testing, packaging, documentation, Git).
• Demonstrated experience analyzing deep sequencing and single-cell data (e.g., Scanpy/Seurat, count models, batch correction, differential analyses).
• Strong grounding in statistics (GLMs, hierarchical/Bayesian modeling, multiple testing) and experimental design principles.
• Bioinformatics workflow design (Snakemake/Nextflow) and HPC/cloud computing.

Prior experience in the following areas is considered a major plus:

• CRISPR screen analysis (pooled or single cell), guide demultiplexing, library design.
• Metagenomics, meta-transcriptomics, and metabolomics data analysis, as well as familiarity with gut microbiome research.
• Machine learning for genomics (representation learning, generative models, causal inference).
• Multi-omics integration (scRNA-seq + CRISPR barcode/perturbation; metagenomics/meta-transcriptomics/metabolomics; transcriptomics/proteomics).
• Genome-scale metabolic modeling applied to individual microbes and their communities.

Workplace

The position is based in the Department of Biosystems Science and Engineering (D-BSSE) at ETH Zurich in Basel, Switzerland. The D-BSSE is a highly interdisciplinary department specializing in systems and synthetic biology, bioinformatics, data science, and engineering sciences. It is centrally located within a biomedical research hub, closely linked to prominent academic institutions and major biotechnology and pharmaceutical companies. The ETH Zurich is globally recognized as a leader in science and technology, consistently ranking among the top universities worldwide. Basel, located on the border with France and Germany, offers a vibrant international atmosphere and easy access to arts, culture, nature, and short commutes throughout Europe.

We Value Diversity

In alignment with our values, ETH Zurich encourages an inclusive culture. We advocate for equality of opportunity, value diversity, and foster a working and learning environment where the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to learn how we create a fair and open environment that enables everyone to thrive.

Curious? So Are We!

We look forward to receiving your online application using the form below. Only applications matching the job profile will be considered.

• Cover letter that articulates your scientific interests and motivation for joining our group.
• Curriculum Vitae (CV).
• Diplomas and course transcripts.
• Contact details of three referees.

For further information about the department, please visit our website. Questions regarding the position should be directed to Prof. Platt at rplatt@ethz.ch (no applications).

About ETH Zurich

ETH Zurich stands as one of the world’s leading universities specializing in science and technology. We are renowned for our excellent education, cutting-edge fundamental research, and direct transfer of new knowledge into society. With over 30,000 people from more than 120 countries, our university fosters independent thinking and inspires excellence. Situated in the heart of Europe while connecting globally, we collaboratively develop solutions for the pressing challenges of today and tomorrow.