Internship - Agentic AI for Computational Biology (all genders) - Inklusiver Job

As an Intern in Agentic AI for Computational Biology, you will contribute to cutting-edge research at the intersection of artificial intelligence and life sciences. Your primary responsibilities include: - Developing and implementing agentic AI models to solve complex problems in computational biology, such as protein structure prediction, drug discovery, or genomic data analysis. - Collaborating with a multidisciplinary team of scientists and engineers to design experiments, analyze results, and iterate on AI-driven approaches. - Building and maintaining pipelines for processing large-scale biological datasets, ensuring data quality and reproducibility. - Conducting literature reviews to stay current with advancements in AI, machine learning, and computational biology, and applying relevant techniques to ongoing projects. - Writing clean, efficient, and well-documented code in Python or similar languages, using frameworks like PyTorch, TensorFlow, or JAX. - Presenting findings and progress to team members and stakeholders through reports, presentations, and code reviews. - Participating in brainstorming sessions to identify novel applications of agentic AI in biological research, including autonomous experimentation and hypothesis generation. - Assisting in the preparation of research papers, patents, or technical documentation for internal and external dissemination. - Adhering to ethical guidelines and best practices in AI research, including fairness, transparency, and data privacy. This internship offers hands-on experience in a dynamic research environment, where you will contribute to projects that have the potential to impact healthcare and life sciences. You will work closely with mentors who are experts in AI and biology, gaining exposure to state-of-the-art computational methods and real-world biological challenges.

To succeed in this role, you should have: - Currently enrolled in a Bachelor's, Master's, or PhD program in Computer Science, Computational Biology, Bioinformatics, Artificial Intelligence, or a related field. - Strong programming skills in Python, with experience in machine learning libraries such as PyTorch, TensorFlow, or scikit-learn. - Foundational knowledge of machine learning concepts, including deep learning, reinforcement learning, or natural language processing. - Familiarity with biological data types (e.g., genomic sequences, protein structures, or omics data) and basic computational biology methods. - Experience with version control (e.g., Git) and collaborative development workflows. - Excellent analytical and problem-solving skills, with the ability to work independently and in a team. - Strong written and verbal communication skills in English. - Preferred qualifications: Experience with agentic AI frameworks (e.g., LangChain, AutoGPT), knowledge of molecular biology or biochemistry, and prior research experience in computational biology or AI.

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