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 at the forefront of developing genome engineering technologies and applying them across a spectrum of fundamental and disease-focused research. To drive these initiatives forward, the Platt group is seeking a full-time (100%) Postdoctoral Associate to advance computational methods for innovative experimental functional genomics datasets.

Project Background

Our laboratory constructs high-throughput experimental platforms necessitating the development of equally cutting-edge computational techniques. The candidate will contribute significantly to two primary areas:

• In vivo single-cell CRISPR perturbation screens
  CRISPR perturbation screens, including Perturb-seq, are revolutionizing the study of gene function at scale. We have recently developed an AAV-based methodology for direct in vivo single-cell CRISPR screening (Santinha, Nature, 2023) and are expanding this work to generate in vivo cell-type perturbation atlases, examine disease mechanisms, and identify therapeutic targets. This work will produce extensive and rich perturbation datasets, necessitating the creation of sophisticated methods integrating machine learning and modeling.
• Transcriptome recording and cellular history reconstruction
  We are enhancing our CRISPR-based transcriptional recording method (Schmidt, Nature, 2018; Tanna, Nature Protocols, 2020), which encodes transient cellular events into DNA and interprets them via sequencing. Key computational challenges involve the detection of biological signals while applying Record-seq to complex in vivo settings (Schmidt, Science, 2022), particularly regarding drug-host microbiome interactions, necessitating the development of specialized tools for the novel data modality produced by Record-seq.

Job Description

We are in search of a highly motivated and collaborative researcher to join our team. The selected candidate will work within a multidisciplinary environment, exhibiting a passion for science, technology, collaboration, and effective communication. Responsibilities will include close collaboration with laboratory members (both experimental and computational) in planning projects, developing computational methodologies, analyzing and integrating omics datasets, and interpreting findings.

The candidate will primarily engage in the following activities:

• Develop analysis methods and provide guidance on experimental design (target gene selection, power analyses, guide-library design, readout selection).
• Construct, maintain, and document reproducible analysis pipelines (Python/R; Snakemake/Nextflow preferred) for novel experimental methods.
• Create 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. Tools employed will include Python, R, version control (Git), and HPC schedulers.

Profile

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

Essential qualifications include:

• Proficiency in Python and R with solid software engineering practices (testing, packaging, documentation, Git).
• Demonstrated experience in 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.
• Experience in bioinformatics workflow design (Snakemake/Nextflow) and HPC/cloud computing.

Prior experience in the following areas will be advantageous:

• CRISPR screen analysis (pooled or single-cell), guide demultiplexing, library design.
• Analysis of metagenomics, meta-transcriptomics, and metabolomics data, along with familiarity with gut microbiome research.
• Machine learning applications in 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 in single microbes and their communities.

Workplace

The position is located 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 and data science, and engineering sciences. It is centrally located within a biomedical research hub, closely linked to esteemed academic institutions (e.g., Swiss Institute of Bioinformatics, Friedrich Miescher Institute (FMI), Biozentrum, and University of Basel) and major biotechnology and pharmaceutical companies (e.g., Novartis, Roche, Bayer, and Lonza). ETH Zurich is recognized as a global leader in science and technology, consistently ranked among the top universities worldwide. Basel is an international city situated on the borders of France and Germany, nestled between the Swiss Alps and the Black Forest, offering easy access to arts, culture, nature, and short commutes throughout Europe.

We Value Diversity

In alignment with our values, ETH Zurich fosters an inclusive culture. We advocate for equal opportunity, value diversity, and nurture a working and learning environment where the rights and dignity of all our staff and students are respected.

Apply Online

We invite you to apply online using the form below. Only applications matching the job profile will be considered.

We look forward to receiving your application. Please include:

• Cover letter expressing 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. Any inquiries regarding the position can be directed to Prof. Platt at rplatt@ethz.ch (no applications).

About ETH Zurich

ETH Zurich stands among the world’s leading universities in science and technology. We are known for our premier education, groundbreaking research, and the direct application of new knowledge to society. More than 30,000 individuals from over 120 countries consider our university a place that nurtures independent thinking and inspires excellence. Situated in the heart of Europe, we forge connections around the globe, working collaboratively to develop solutions for today’s and tomorrow’s global challenges.