- Proposing, implementing, and optimizing state-of-the-art single cell analysis workflows in support of discovery projects
- Ensuring and facilitating effective generation and communication of data, insight and knowledge within the team and across pRED
- Nurturing reproducible and unbiased data-driven discovery guided by best-practices in the field
- Master, PhD or Post Doc in Bioinformatics, computational biology, data science
- 2 to 3 years hands of relevant experience
- Proven experience with standard scRNAseq workflows such as Seurat/Scanpy/OSCA, and with conventional steps involved in analyzing scRNAseq data.
- Programming language proven experience with R
- You have a keen interest to follow the relevant literature and explore/implement the most recent developments in the field.
- You are resourceful and flexible in problem solving and in working in a collaborative environment that gives you full accountability for your own contributions and development.
- You are able to identify your top deliverables, finalize projects to achieve results whilst assuming personal responsibility for outcomes.
- Knowledge of Python
Company
Location
Zürich - Switzerland
Job type
Full-Time
Python Job Details
EINFÜHRUNG:
As a preferred supplier for Roche Basel (offices in Zurich), we are looking for an individual as
Single Cell Data Analyst
(contract for 1 year, with possible extension). The earliest start date is within 3 months.
As a preferred supplier for Roche Basel (offices in Zurich), we are looking for an individual as
Single Cell Data Analyst
(contract for 1 year, with possible extension). The earliest start date is within 3 months.AUFGABENBESCHREIBUNG:
As a single cell data analyst you will be primarily working on single cell genomics datasets (mostly sc-RNA and CITE-seq, maybe sc-ATAC) of tumor and blood specimens obtained from large cohorts of patients and preclinical experiments treated with T cell bispecifics and/or other cancer immunotherapies. You will work closely with other data scientists and bioinformaticians within CIT Discovery, and will also be part of an internal network of data scientists within pRED.
ERFORDERLICHES PROFIL:
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