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Biologist

Employer
Cynet Systems
Location
Grand Central, New York, US
Salary
Competitive
Closing date
Aug 7, 2024
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Sector
Academic / Research
Field
Informatics / GIS
Discipline
Modeling
Salary Type
Salary
Employment Type
Full time
Job Description:

Pay Range $44.21hr - $49.21hr

Responsibilities:
  • The Scientist will support the development of Client therapeutic candidates by performing hands-on, bench-level research involving bacterial, mammalian cell culture, and molecular biology experiments, as well as sample processing and analyses from in vivo animal studies.
  • The successful candidate will work with the Genome Engineering and Modeling team to generate new DNA constructs for testing, process samples from in vitro / in vivo experiments, assist in data analysis, and manage sample inventory.
  • The ideal candidate will be a team player, with strong organizational, interpersonal, and communication skills.
  • Carry out in vitro studies and support sample processing and analysis from in vivo studies.
  • Molecular cloning to generate new DNA constructs for testing.
  • Perform expression analysis at the mRNA, and protein level.
  • Prepare and run libraries for next-generation sequencing (NGS).
  • Manage sample inventory and a detailed notebook describing experimental methods/results.
  • Train new team members in the use of equipment, laboratory procedures, and protocols as needed.
  • Critically assess data generated from diverse experimental approaches in cell and molecular biology.
Qualifications:
  • PhD with 3+ years of laboratory research experience in academia/industry.
  • Experience performing basic techniques in molecular biology and cell biology, such as PCR, molecular cloning, and mammalian cell culture.
  • Ability to think critically and creatively in a fast-paced, highly collaborative scientific environment.
  • Prior research experience constructing and working with high-complexity DNA libraries.
  • Experience in gene therapy and neuroscience research.
  • Comfortable with Illumina sequencing and familiar with downstream bioinformatics pipelines.
  • Experience with high throughput screening strategies and experimental techniques.

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