Scientist / Senior Scientist (f / m / d) 80-100%

Gi Group SA; Basel; Remote; CHF 80.000 - 120.000; Vollzeit

Zusammenfassung

An established industry player is seeking a talented computational biologist to lead innovative research initiatives. This role involves developing in silico experimental designs and performing advanced analytics to derive meaningful biological insights. The ideal candidate will have a strong background in genetics and extensive experience with programming in R and Python. Join a dynamic team where you will collaborate with both computational and wet-lab scientists, contribute to cutting-edge projects, and help democratize access to data and analytics in a supportive environment. If you are passionate about translating complex scientific data into actionable insights, this opportunity is perfect for you.

Qualifikationen

• 5+ years of postdoctoral experience with industry experience preferred.
• Strong background in genetics and statistical analysis of large datasets.

Aufgaben

• Lead data-driven research and develop computational analyses for sequencing-based assays.
• Collaborate with scientists and manage multiple projects effectively.

Kenntnisse

Programming in R

Programming in Python

Statistical analysis

Data visualization

Algorithm development

Data mining

Machine learning

Graph theory

Bayesian methods

Mendelian Randomization

Ausbildung

PhD in a relevant discipline

Tools

Linux/Unix

HPC environments

Shiny

Jobbeschreibung

Tasks & Responsibilities:

• Lead in developing in silico experimental design and operate a data-driven research group.
• Perform rigorous advanced analytics exploration of data from disease areas of strategic relevance.
• Report emergent biological insights to stakeholders in a reproducible manner.
• Facilitate access to enterprise data and analysis tools for non-data scientists.
• Develop, customize, and perform computational analyses and algorithms for raw data from sequencing-based assays (e.g., whole genome/exome sequencing, single-cell and bulk RNA-seq, proteomics, genome-wide phenotypic screens).
• Pre-process raw datasets, conduct high-level analysis, and visualize data to interpret and derive new biological insights.
• Collaborate with group members and internal partners to analyze large-scale datasets.
• Validate and optimize emerging computational research tools.
• Support research collaborations with experimental scientists.
• Develop and maintain tools and applications (e.g., Shiny).
• Create and implement standardized workflows and pipelines.
• Manage data, ensure standardized reporting, and promote democratized access to data and analytics in line with FAIR principles.
• Contribute to peer development curricula for workshops and training sessions.
• Work effectively in matrix teams, providing leadership and participating as needed; build and maintain stakeholder relationships across the organization.
• Analyze and integrate complex scientific information into higher-level understanding, translating concepts into actionable hypotheses.

Must Haves:

• PhD in a relevant discipline.
• At least 5 years of postdoctoral experience, including industry experience if applicable.
• Ability to work across scientific domains, diseases, and biological scales with creativity.
• Proficiency in programming/scripting in R and/or Python; working knowledge of Linux/Unix, experience in HPC environments, and basic systems administration understanding.
• Experience collaborating with wet-lab scientists and managing multiple projects with shifting priorities.
• Strong statistical, reporting, and data visualization skills; emphasis on data, code, and project hygiene.
• Solid genetics background, including experience with Mendelian Randomization, GWAS, and integrative analyses such as proteogenomic modeling.
• Expertise in graph theory and network-based approaches to biological data, including disease modeling, graph search tools, and graph learning; familiarity with Bayesian and/or logic networks.
• Experience in integrating and visualizing multimodal data from clinical and model systems.
• Skills in algorithm development, data mining, and statistical analysis of large datasets, including Bayesian methods, Markov models, simulation, and machine learning.
• Experience handling, integrating, and visualizing multimodal data (e.g., CITE-seq, spatial transcriptomics, proteomics, metabolomics).

Nice to Have:

• Knowledge of additional programming platforms.
• Experience in signal transduction and perturbation modeling.

General Information:

• End date: 30.09.2025
• Location: Basel
• Remote/Home Office: To be discussed

Your Application:

Please apply online. For more information, contact your Kelly recruiter, Fatbardha Igrishta, at [e-mail].