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engineering, structural dynamics, basic isolation, finite element modelling. Proficiency and/or interest in programming languages (e.g. MATLAB, Python, R) and software platforms such as OpenSees, ABAQUS, LS
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computer science, bioinformatics or related fields Solid understanding of machine and deep learning and relevant frameworks (e.g. Pytorch or Tensorflow, Keras, scikit-learn, OpenCV) Proficiency in Python, Linux and
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(e.g. python, R); affinity and experience with performing animal experiments; experience with classical biological methods (e.g. dissections, immunohistochemistry, western blot, PCR, in vitro assays
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scientific programming (e.g. Python, MATLAB, or R) for data analysis and visualization A clear affinity for insect behavior, sensory ecology, or movement ecology; Fieldwork experience or a strong interest in
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infrastructure, semantic technologies, and applied research Solid programming experience, preferably in Python Familiarity with structured data handling (e.g., SQL) and scientific workflows A two-year MSc degree
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to engage in interdisciplinary collaboration and teaching. Good programming capabilities in advanced analysis software (e.g., Python, R, MATLAB, Julia, or similar) and mathematical optimization suites
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programming capabilities in advanced analysis software (e.g., Python, R, MATLAB, Julia, or similar) and mathematical optimization suites (e.g., GAMS, Pyomo, JuMP, or similar). Besides that, your ability and
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Energy simulation software, such as TRNSYS, Modelica, EnergyPro Programming languages, such as Python Ability to communicate results in technical reports, and prepare scientific papers for publication in
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assistantship. The ideal candidate will have a strong understanding of NLP, machine learning, and AI ethics, with proven skills in Python and frameworks like TensorFlow or PyTorch. Preference may be given
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literacy and basic programming skills (R, Python), or the willingness to develop these skills Analytical mindset, with a keen interest in advancing proteomic methodologies We offer Cutting-edge proteomic