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The Senior IT Engineer I - Labs will maintain laboratory IT infrastructure, develop strategies for stakeholder engagement, implement solutions for data capture and storage, and enhance system performance. This role requires extensive collaboration with research teams and internal IT departments.
The Global Safety Lead is responsible for developing safety strategies and overseeing safety deliverables for products. This role involves collaboration with cross-functional teams to establish safety profiles, conduct safety surveillance, chair safety committees, and communicate safety information to stakeholders, ensuring patient safety throughout clinical trials.
Interns will work closely with experienced professionals on liquid chromatography-mass spectrometry analysis, biological sample preparation, and ADME research in a collaborative environment. Opportunities are provided for personal and professional development, culminating in presentations at group meetings.
The Director - Global Regulatory Lead will lead a global regulatory team in developing and executing regulatory strategies for drug development, ensuring high-quality regulatory deliverables and effective communication with stakeholders. This role involves managing health authority interactions, overseeing global filing activities, and maintaining knowledge of regulatory landscapes while fostering team development and accountability.
The Operational Excellence intern will support project plans, prepare meeting updates, conduct data analysis, and assist with presentations in a collaborative environment within the US R&D Operations team.
The Bioinformatics intern will develop computational pipelines and process next-generation sequencing data to support RNA interference target screening. Responsibilities include data cleaning, developing a metadata database, creating an R package for bioinformatics reporting, and processing single-cell RNA-sequence data for visualization.
As an intern in the machine learning department, you will assist in building and refining machine learning models using structured and unstructured clinical data. Responsibilities include data preprocessing, feature engineering, model training, and implementing NLP algorithms to extract insights from clinical text data, while collaborating with other data scientists.
The Data Engineer intern will assist the Imaging Solutions product team in building imaging data pipelines for drug discovery. Responsibilities include collaborating with scientists, analyzing phenotypic data, and troubleshooting issues while participating in team meetings and reviews.
The internship focuses on improving property prediction for drug discovery using advanced computational methods. Responsibilities include data preprocessing, model design, and evaluation of results, with an emphasis on applying machine learning techniques to real-world challenges.
The Oligonucleotide Bioanalysis intern will learn and support method optimization for PNA based hybridization assay using HPLC-FD or LC-MS for siRNA quantification. The role includes presenting work progress at meetings and writing a report at the end of the internship.
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