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Field
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studies, QTL studies, colocalization, Mendelian Randomization) Proficient in R, Python, Linux/Unix Command over commonly used genetics (e.g., PLINK, GCTA, FUMA, variant predictor tools) and metagenomics
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and conferences. Proven experience in design and implementation of deep learning algorithms. Outstanding programming skills in Python. Extensive experience working on one or more of the following areas
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desirable. Proficient in Python, R, and ML libraries such as PyTorch or TensorFlow. Strong communication and collaboration skills; ability to work independently and as part of a team. Willingness to respect
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- maximum 5 points); c) Knowledge of Python languages (maximum of 5 points) d)Mastery of the English language, to be assessed through a motivation letter (maximum of 5 points) The curriculum of each candidate
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house/growth chambers) and wet lab research experience. Expertise in statistical packages (SAS), R, Python, or similar programming skills. Point of Contact Janeen Eligibility Requirements Citizenship: LPR
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Python and relevant libraries. Desired Qualifications* Prior experience with genomic data modeling. Interest or experience working in neuroscience domain applications. Strong interpersonal and
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Demonstrated proficiency with Python, and machine learning libraries; pytorch, sklearn Experience with transformer architectures, and interpretable AI methods and libraries, concept-bottleneck architectures
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. Preferred Knowledge, Skills, and Abilities: Experience of method development in quantum chemistry. Demonstrable coding experience for example with python, fortran, C++ or others. Experience in modeling
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programming skills (e.g., Python, MATLAB, R) experience with large datasets desirable proficiency in English, both written and spoken (at least C1) German is an advantage willingness to work regularly on-site
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language proficiency sufficient for reading and writing academic texts (B2+/C1) strong teamwork orientation and good communication skills Preferred qualifications: programming languages (e.g., Python