Scientist/Sr. Scientist, Translational Medicine

Scientist/Sr. Scientist, Translational Medicine

Philadelphia, PA

About the Position

At Cabaletta Bio, we are focused on delivering cellular therapies to treat autoimmune disease indications. The translational medicine group works closely with both clinical operations and computer biology teams to ensure that data from clinical stage assets is accurate and of the highest standards. Reporting to the Associate Principal Scientist, Translational Medicine, we are seeking an experienced, motivated, detail-oriented, and highly skilled Scientist or Sr. Scientist within our translational team.

Under scientific and technical supervision, the individual will design, optimize, and perform assays that characterize Cabaletta's clinical-stage candidates. Specific responsibilities include the implementation and execution of multi-parameter flow cytometry and cell-based assays intended to evaluate pre- and post- characteristics of the clinical assets. Additionally, multiplex assays will be used on serum samples to measure immune-related factors for changes in disease signatures. As part of the Translational Medicine team, the individual must be able to perform qualified assays on clinical trial participant materials, adhering to internal compliance standards. The individual may assist the Associate Principal Scientist in devising and implementing strategies for ad hoc investigations that arise throughout candidate testing. The position allows for collaboration with additional Cabaletta research teams, including preclinical and molecular biology, cellular immunology, and next-gen cell therapy development.

Responsibilities Include

• Design and/or perform high-dimensional flow cytometry assays for the analysis of clinical samples.

• Design and/or perform cell-based assays, including cell cytotoxicity and ELISPOT.

• Qualify assays and generate high-quality SOPs while working closely with quality assurance (QA) team members.

• Manage multiple internal projects for the Translational team with potential support across functional teams, as well as involvement in collaborations with external vendors.

• Actively contribute to process improvements and the implementation of new technologies.

• Perform lab associated tasks in accordance with cGLP and Cabaletta Bio lab safety policies and SOPs.

• Maintain accurate and well-organized records and electronic laboratory notebook.

• Support clinical sample management and tracking of incoming patient samples.

• Maintain detailed oriented notes and records for clinical sample lifecycle (receipt, usage, etc.).

Required Qualifications

• Minimum PhD degree in Immunology or Biology (or related field) or MS with 2-3 years related experience

• Strong background in Immunology, B and T cell biology,

• General lab skills, including aseptic techniques and human tissue handling.

• Expertise in flow cytometry high-dimensional panel design and implementation.

• Must be highly organized and able to work independently.

• Must be able to clearly communicate in writing.

• Encompass a desire to be part of a growing organization that uses cutting-edge science.

• A high level of flexibility to support various other activities and the ability to learn new techniques outside of existing field of expertise.

• Strong team orientation and passion for continuous self-development.

• Strong time management skills and ability to prioritize work across projects according to company objectives.

Preferred Skills

• Previous experience with GLP/GCP work and handling of clinical samples is preferred.

• Clinical sample inventory management/LIMS experience.

• Experience with ELISPOT and Meso-scale Discovery electrochemiluminescence assays.

• Experience in cytotoxicity assays (such as IncuCyte, xCELLigence, 51Cr or luciferase-based assays).

• Translational experience in an industry setting.

• Comfortable working in fast paced environment.

• Strong team orientation and passion for continuous self-development.

• Experience in the biotech industry or in a startup industrial setting is preferred.

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