Research Assistant III- Diagnostics Accelerator

The Wyss Institute for Biologically Inspired Engineering at Harvard University

Boston, MA

Job posting number: #7110737

Posted: September 15, 2022

Application Deadline: Open Until Filled

Job Description

About us:

The Wyss Institute’s mission is to transform healthcare and the environment by emulating the way nature builds. We harness the freedom of academia and the focus of industry in order to translate revolutionary technologies into commercial products and solutions. At the Wyss Institute, faculty from premier academic and clinical institutions, collaborate with staff scientists, postdocs, graduate students, industry experts, business development leaders, and entrepreneurs across disciplines to invent and de- risk new technologies that don’t just succeed at making it to the market – they disrupt it. We support research that universities, companies, and venture capital firms don’t fund because they view it as too risky. We prefer to use the word “challenging,” and we love challenges. For more information, visit: http://wyss.harvard.edu/



About you:

You are a collaborative, impact-focused problem solver who wants to be part of a dynamic team dedicated to creating and commercializing novel approaches to global challenges in healthcare and sustainability. You want the freedom to explore, to push the boundaries of what is possible, and to use your ambition to tackle challenging projects in a fast-paced, industry-focused environment without a lot of administrative hurdles. You enjoy working with diverse groups of people and leveraging your expertise to create innovations that can change the world.


About the role:
We are looking for a motivated, enthusiastic Research Assistant III to join our team in the newly established Wyss Diagnostics Accelerator. You will work with a multidisciplinary team involving several faculty members at the Wyss Institute working on the development of molecular diagnostics. The Wyss Diagnostics Accelerator is involved in several projects developing new technologies for diagnostics and the application of these technologies to several disease areas (infectious diseases, neurology, and others).



This position is for someone who is excited about science and enjoys working at the bench. Although you will work within a team and receive significant experimental training, you will also have significant opportunities for scientific independence and managing your own subprojects. For candidates with computational skills and interests, there will also be opportunities for analyzing high-throughput NGS and proteomics data.


What you’ll do:
- Develop expertise in new and established techniques for profiling of protein and nucleic acid biomarkers from human biofluids, including protein measurement using mass spectrometry and Single Molecule Arrays (Simoa) digital ELISA technology, as well as Next Generation Sequencing (NGS) for the analysis of circulating nucleic acids.
- Work in collaboration with senior lab members to establish automation using liquid handling instruments.
- Provide training and guidance to other lab members on experimental technique
- Perform lab maintenance such as maintaining and/or purchasing equipment and ordering supplies, as required
- Present data at internal Wyss meetings with supervision from senior lab members
- Demonstrate a commitment to diversity, inclusion, and cultural awareness through actions, interactions, and communications with others.

What you'll need:
- Bachelor’s degree in a biological science or related field and two or more years of lab experience in molecular biology or biochemistry, including experience with nucleic acid analysis and/or protein biochemistry, is required. Advanced degree may count towards years of experience.

Experience with one or more of the following is advantageous but not required:
- Mass spectrometry
- Protein quantification using ELISA
- Next generation sequencing (NGS) library construction
- Programming of liquid handling robots
- Programming experience (Python or R) and expertise in computational analysis of large biological datasets.



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