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    Junior
    31.10.24

    PhD - Deep Learning and Perturbation Models (f/m/x)baito Pro Job

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    Einführung

    Join Helmholtz Munich as a Doctoral Researcher in a collaborative project with Pfizer Inc., focusing on deep learning and perturbation models for target discovery and precision medicine.

    Aufgaben

    • Curate, prepare, and analyse immune cell CRISPR data.
    • Integrate large-scale clinical omics data and meta data from public and private clinical studies.
    • Support with the development of deep learning algorithms to compare human diseases and preclinical models.
    • Model both genetic and chemical perturbations in out-of-distribution conditions.

    Voraussetzungen

    • Major in one of the biological sciences, computer science, math, physics, chemistry, etc.
    • Proficiency in programming languages such as Python
    • Experience in analysing and integrating large-scale omics data (e.g., RNA-seq, bulk transcriptomics, single-cell data) and applying machine learning methods
    • Ability to work collaboratively in a multidisciplinary team
    • Interest in obtaining a Ph.D. in Computational Biology with a focus on machine learning, deep learning, or artificial intelligence.
    • Research experience in developing, applying, and evaluating deep learning algorithms (preferred)
    • Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) (preferred)
    • Familiarity with perturbation models, genetic perturbations, and compound data (preferred)
    • Good publication record (preferred)

    Benefits

    • Scientific Training: Helmholtz Munich Graduate School
    • Career counseling: Career Center for PhD candidates
    • Recreation: 30 days annual leave, flexi days, plus public holidays
    • Health Promotion: Sports, company doctor, mental health initiatives
    • International Staff Service: Support with the relocation and integration process in Germany

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