Student Placement - Machine Learning / Computational Biology Scientist

Job Description

The qualified individual will have experience in a STEM (Science, technology, engineering, and mathematics) discipline and an interest in applying their expertise in the field of biological research. They will be responsible for helping us develop discovery pipeline by applying/augmenting data science and systems biology approaches to address questions in drug discovery e.g. target discovery, biomarker discovery, biological network analysis etc.

The person in this role will be expected to operate in a collaborative matrix environment, working with cross-functional teams of computational biologists, data scientists, bench scientists. You will be a part of a diverse and global team tightly integrated within highly collaborative multidisciplinary scientific environment at our London site, interacting with leading academic groups and research centres across the UK/EU. Due to our diverse work, projects and responsibilities can be tailored to the applicant’s strengths and interests.

We are a global biopharmaceutical leader committed to enhancing the lives of individuals through a diverse portfolio of prescription medicines, oncology treatments, life-saving vaccines, and animal health products. Our unwavering dedication to delivering innovative solutions is the driving force behind everything we do. With a team of over 70,000 employees spread across 140+ countries, we offer state-of-the-art laboratories and inspiring offices designed to foster growth and development in our team members.

Responsibilities:

• Use machine learning toolkits to augment target and biomarker discovery efforts
• Use computer vision and deep learning methods to integrate multi-omics data in order to link them to disease phenotypes
• Work with knowledge graphs to improve discovery of novel disease mechanisms
• Advance the use of natural language processing (NLP) tools to improve understanding of diseases and therapeutic targets
• Use computational biology, bioinformatics and network biology to answer biological questions

Requirements:

• You must currently be at university and will be looking to complete a 12-month student internship as part of your undergraduate degree.
• Strong interest in one or more: applying data science, computational biology or machine learning to solving biological questions
• Demonstrable experience in applying statistical methods to analyse data and interpreting results
• Experience in coding (python and/or R)

Deadline:

Monday 7th October 11:59pm 2024

Next Steps:

In the event of your successful progression to the next stage, one of our future talent team will contact you within two - three weeks of the application closing date. 

Start Date:

June 2025

Equal Opportunity Employer:

We are proud to be a company that embraces the value of bringing diverse, talented, and committed people together.

For more Information visit our Future Talent page!

#ukft2024

Current Employees apply HERE

Current Contingent Workers apply HERE

Search Firm Representatives Please Read Carefully 
Merck & Co., Inc., Rahway, NJ, USA, also known as Merck Sharp & Dohme LLC, Rahway, NJ, USA, does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place for this position will be deemed the sole property of our company.  No fee will be paid in the event a candidate is hired by our company as a result of an agency referral where no pre-existing agreement is in place. Where agency agreements are in place, introductions are position specific. Please, no phone calls or emails. 

Employee Status:

Relocation:

VISA Sponsorship:

Travel Requirements:

Flexible Work Arrangements:

Shift:

Valid Driving License:

Hazardous Material(s):

Job Posting End Date:

*A job posting is effective until 11:59:59PM on the day BEFORE the listed job posting end date. Please ensure you apply to a job posting no later than the day BEFORE the job posting end date.