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PhD degrees in the field of life sciences (biology, molecular biology, biochemistry, biophysics, structural biology, genetics, bio-engineering, bioinformatics, etc. The Scientist on the Bioengineering team will be responsible for leading activities in the bioengineering, fermentation and process development areas.
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More than 130 faculty members serve nearly 4,000 undergraduate, graduate and PhD students across six departments: bioengineering, chemical and petroleum engineering, civil and environmental engineering, electrical and computer engineering, industrial engineering, and mechanical engineering and materials science.
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Currently enrolled in university, pursuing a Master's degree, PharmD, or PhD in Engineering (Chemical, Biomedical/Bioengineering, Material Science), Physical or Biological Sciences, or other related field.
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PhD in a relevant discipline such as: computer science, math, computer engineering, statistics, cognitive science, electrical engineering, bioengineering, data science, etc. PhD in a relevant discipline such as: computer science, math, computer engineering, statistics, cognitive science, electrical engineering, bioengineering, data science, etc.
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Job Requirements: PhD degree, or foreign equivalent, in Electrical Engineering, Computer Science, Statistics or Bioengineering or a related field plus 3 years as a Data Scientist or any job title/occupation/position involving Data Sciences.
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PhD in Engineer, Bioengineering, Biochemistry, or Molecular Biology strongly preferred. Bachelor’s degree in Engineering, bioengineering, Microbiology, synthetic biology or related discipline.
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You have a Bachelor's, Master's, or PhD in Analytical Chemistry, Biochemistry, Chemical Engineering, Bioengineering, or a related field. You have a proven track record in lateral flow assay development (other keywords include: lateral flow immunoassays (LFA), In Vitro Diagnostics (IVD), point-of-care diagnostics, rapid diagnostic tests, paper-based sensors, biosensors, microfluidic.
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PhD in a scientific discipline and a minimum of 5 years related experience; may include post-doctoral experience; Masters and 7 years of related experience; Bachelors and 9 years of related experience in data engineering, systems engineering, machine learning and operations, MLOps, or similar roles; or equivalent industry experience.
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Relevant PhD degree required in computational biology, computational neuroscience, applied mathematics, computer science, or related discipline required, with a strong bioengineering and/or molecular biology focus.
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As Computational Scientist , you will be a critical senior member of a collaborative team that develops cutting edge computational methodologies and technologies in order to understand the mechanisms of neuroimmunology, cancer immunology and aging, in an efficient and comprehensive manner, which will accelerate the advancement of clinical therapeutic hypotheses.
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Independently design experiments with an exceptional variable control for lateral flow assay development and optimization. You have 5+ years of assay development experience in the industry. Hormones are at the core of our health, yet they remain a black box.
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Eli is looking for a R&D Scientist III. You will be a key member of our R&D team, helping to discover new ways to improve current and future iterations of our assay technology. Act as a technical leader for the lateral flow development team and mentor associates through assay design, development, and optimization.
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We are looking for a highly motivated researcher with a PhD in bioengineering, biophysics, quantitative biology, molecular biology, or closely related field, who is passionate about interdisciplinary research and working at an undergraduate institution.
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Diversity is ingrained in our company DNA. Currently, 80% of Eli's team identify as women and 60% as part of another minority group. You have brought assays through key points in their life cycles (conception, verification, manufacturing, commercialization, etc.
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As one of the first members of this new team, you will have a large role in molding our approaches to creating foundation models for biology, as well as creating fine-tuned and derived models for specific applications in bioengineering.
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