2021 Summer Intern Computational Biology at Takeda – Apply
2021 Summer Intern Computational Biology at Takeda – Apply. As one of the world’s leading biopharmaceutical companies, Takeda is committed to bringing Better Health and a Brighter Future to people worldwide. We aspire to bring our leadership in translating science into life-changing medicines to the next level, in our core focus areas; oncology, gastroenterology, neuroscience, rare diseases, plasma-derived therapies, and vaccines.
Job ID: R0025675
Location: Cambridge, Massachusetts
Worker Type: Employee
Worker Sub-Type: Paid Intern (Fixed Term) (Trainee)
Time Type: Full time
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Job Description
POSITION OBJECTIVES:
Takeda’s summer internship program blends real-world experience with an extensive overview of the pharmaceutical industry. We look for a summer intern who wants to work on machine learning, deep learning, and AI for drug discovery and development. Knowledgeable mentors will provide guidance as you gain professional hands-on experience. The summer internship program is 12 weeks in length and offers a unique perspective into a world-class pharmaceutical company. Compensation is competitive, and financed temporary housing is available to those who qualify. Our internship program also provides you with the opportunity to network with people at Takeda through various planned events and activities.
POSITION ACCOUNTABILITIES:
- Will assist to evaluate machine learning/deep learning/artificial intelligence methods for biomedical data analysis
- Will run a literature search/review and algorithm evaluation with strong statistical and quantitative skills
- Will write reports and give presentations on the analysis results to internal/external audience
- Experience in each of the following MS Office applications:
- MS Outlook – Proficient
- MS Word – Proficient
- MS Excel – Proficient
- MS PowerPoint – Proficient
- Must be deadline-driven and have a high level of organizational and planning skills
- The ideal candidate exhibits strong analytical, problem-solving, and oral and written communication skills; he or she also possesses the ability to work well in teams, effectively manage multiple projects, and present ideas clearly and concisely.
EDUCATION, BEHAVIORAL COMPETENCIES AND SKILLS:
- A PhD student/candidate or equivalent in computational biology, bioinformatics, computer science, statistics (biostatistics), electrical and computer engineering, biomedical engineering, or bioengineering
- Strong quantitative science background including statistics, machine learning, particularly deep learning
- Extensive experiences with building machine learning-based predictive models using biomedical data such as genomics and patient phenotype data
- Good experiences with analyzing large-scale genomics data including NGS-based mutations and gene expression profiles such as DNA-Seq and RNA-Seq
- Proficient in R and Python. Also proficient in Python-based deep learning development platforms such as Keras, PyTorch, and TensorFlow
- Excellent communication skills and attitude for collaboration