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The Leibniz-Institut für Analytische Wissenschaften - ISAS - e. V. develops efficient analytical methods for health research. Thus, it contributes to the improvement of the prevention, early diagnosis, and therapy of diseases like cardiovascular diseases or cancer. Overall, the institute strives...
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PhD students (multiple positions) Artificial Intelligence within Public Health Research (all genders) Start date: 01.10.2026 Contract type: 3 years (fixed-term) Location: Wildau Deadline: 30.04.2026
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model of immune tolerance, effectively inducing temporary remission in autoimmune conditions like multiple sclerosis. Our goal is to "learn pregnancy’s code" to understand these natural protective
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spectrometry-based phosphoproteomics, redox proteomics (CysQuant), and RNA-sequencing, leveraging VIB's Proteomics Expertise Center. Job description Within a larger project on climate-resilient crops, on healthy
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-friendly environment with multiple actions to attract, develop and retain women in science · 32 days’ paid annual leave, 11 public holidays, 13-month salary, statutory health insurance
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learning approaches to link gene-regulatory programs to neuronal phenotypes.Use explainable sequence-to-function models to interpret regulatory logic underlying neuronal identity and function.Integrate
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Data-Centric AI. We aim to make large-scale ML more reliable, transparent, and aligned with human values. We are specifically interested in: Data-centric AI: Advancing machine unlearning, privacy
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up analytics including HPLC, LC-MS and GC-MS Protein expression, purification and characterization using biochemical and biophysical assays Variant identification using next generation sequencing
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-generation sequencing analysis is a plus Expertise in AI/ML is a plus Experience with job submission systems/HPC is a plus Proficiency in English (oral and written) Excellent organisational skills and ability
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our workforce · Diverse and inclusive work environment empowering our people to fulfil their personal and professional ambitions · Gender-friendly environment with multiple actions