Intern (m/f/d) Computational structural biology and modelling

KWS SAAT SE; Einbeck; Híbrido; EUR 13.000 - 20.000; Jornada completa

Descripción de la vacante

Intern (m/f/d) Computational structural biology and modelling at KWS SAAT SE is a fixed-term, full-time internship based in Einbeck, Germany, with hybrid working within the country. You will benchmark modeling platforms, run workflows on HPC, and document results while collaborating with experimental and computational teams.

Qualification in bioinformatics/structural biology or related field, plus machine learning experience, is expected. Proficiency in English; German is a plus.

Formación

• Qualification in Bioinformatics, Structural Biology, Computer Science, or related discipline.
• Experience in machine learning and interest in foundation models for life sciences.
• Strong documentation and collaboration skills.

Responsabilidades

• Benchmark computational protein modeling platforms.
• Run workflows on HPC infrastructure and analyze performance.
• Document workflows, data, and results in reproducible form (GitLab).
• Present progress in internal project meetings and collaborate with scientists.
• Communicate scientific findings effectively.

Conocimientos

Bioinformatics

Structural Biology

Computer Science

Machine Learning

Foundation models

Herramientas

Nextflow

Snakemake

SLURM

Containers

PyTorch

Hugging Face

AlphaFold

Descripción del empleo

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Intern (m/f/d) Computational structural biology and modelling

Field of Work: Research & Development

Location: Einbeck, Lower Saxony, DE

Legal Entity: KWS SAAT SE & Co. KGaA

Contract Type: Temporary

Is Full Time?: Yes

Onsite/ Remote: Hybrid Working Within Country

Job ID: 16950

Looking to gain valuable hands-on experience at KWS?

At KWS, we are advancing data- and knowledge-driven approaches to develop innovative traits for sustainable agriculture. Within our Trait Discovery activities, computational structural biology and advanced protein modelling are important elements to support the nomination and prioritization of trait candidate genes.

Together with colleagues from Trait Discovery and Data Science, you will benchmark computational methods, curate relevant datasets, and translate model outputs into testable hypotheses for experimental validation.

This full-time internship is offered as a fixed-term position for six months and is based at the KWS SAAT SE & Co. KGaA headquarters in Einbeck, Germany.

Your Key Responsibilities

• Benchmark, validate and update computational protein modeling platforms using internal and publicly available datasets.
• Run computational workflows on high-performance computing infrastructure and analyze model performance, accuracy, and robustness.
• Document workflows, code, datasets, and results in a reproducible manner, for example in a GitLab repository.
• Present progress and findings in internal project meetings and collaborate closely with experimental and computational scientists.
• Qualification in Bioinformatics, Structural Biology, Computer Science, or a related discipline, with experience in machine learning and an interest in foundation models and AI for life sciences
• Technical know-how and hands-on experience in implementation of computational tools in high-performance clusters (e.g., nextflow or snakemake)
• Familiarity with high-performance computing environments and technologies such as SLURM, containers, PyTorch, or Hugging Face is advantageous.
• Experience in applying protein structure-prediction tools like AlphaFold is a plus
• A structured and reliable working style, with a strong focus on documentation, data quality, and reproducibility.
• An open, proactive, and collaborative mindset, combined with the ability to communicate scientific findings effectively.
• Good written and spoken English; German language skills are beneficial.

Further information: https://www.kws.com/corp/en/careers/ .

At KWS, diversity is not just a value; it is an essential part of our success. Breeding resilient crops requires diversity; likewise, our strength comes from the diversity of our teams. Whatever your background or identity is, we invite you to join us.