Match score not available

Intern - Research Scientist - Biopharma Discovery Engine

fully flexible

Remote:

Hybrid

Contract:

Internships

Experience:

Entry-level / graduate

Work from:

Paris (FR), Nantes (FR)

Offer summary

Qualifications:

Enrolled in a master's degree in machine learning, computational biology, bioinformatics, or related field, Authorization to work legally in France, Fluency in English (spoken and written), Strong programming skills in Python with relevant libraries experience, Knowledge of deep learning frameworks and statistical analysis.

Key responsabilities:

Characterize and correct patient-specific batch effects in spatial transcriptomics and single-cell data
Develop robust analytical methods and enhance data integration capabilities
Design new batch effect removal methods specific to Visium spatial transcriptomics
Explore out-of-domain generalization techniques for batch effect removal
Assess performance of learned representations on downstream tasks

Owkin Startup https://owkin.com/

201 - 500 Employees

HQ: New York

See more Owkin offers

Job description

About us

Owkin is an AI biotechnology company that uses AI to find the right treatment for every patient. We combine the best of human and artificial intelligence to answer the research questions shared by biopharma and academic researchers. By closing the translational gap between complex biology and new treatments, we bring new diagnostics and drugs to patients sooner.

Owkin has raised over $300 million and became a unicorn through investments from leading biopharma companies (Sanofi and BMS) and venture funds (Fidelity, GV and BPI, among others).

Owkin is seeking the best and brightest to join our fast-growing and dynamic team.

About the role:

This position is based in Paris, France. Ideally you are able to join the team in Dec 2024, or early Jan 2025. Please submit your CV in English.

At Owkin, we leverage cutting-edge spatial transcriptomics technologies like 10x Visium to understand complex tissue architectures and cellular heterogeneity in cancer patients. Our focus is on developing robust analytical methods that can overcome technical and biological variations while preserving meaningful biological signals. These unwanted technical variations, commonly called “batch effects” can come from various sources: experimental conditions, sample preparation, sequencing platform, …

Specifically, you will work on characterizing and correcting patient-specific batch effects in spatial transcriptomics (Visium) and single-cell data, while ensuring the preservation of biological signals critical for downstream analyses. Under the leadership of your mentor(s), your work will directly contribute to improving Owkin's internal pipelines to:

Develop more robust and generalizable analytical methods
Enhance cross-center data integration capabilities
Improve patient stratification through better data harmonization

In particular, you will:

Explore and assess the presence of batch effects in MOSAIC spatial transcriptomics data
Design new batch effect removal methods specific to Visium spatial transcriptomics data and compare them to existing methods
Explore out-of-domain generalization (OODG) techniques and see how they apply to batch effect removal on Visium spatial transcriptomics data (batch correction and OODG are two domains that have largely independent literature). The performance of the learned representations could be assessed on the downstream tasks in both in-domain and out-of-domain (OOD) settings.

About you

Required qualifications / experience:

You are enrolled in a master degree in machine learning, computational biology, bioinformatics, computer science, or related field
Authorization to work legally in France
Fluent in English (spoken and written)
Strong programming skills in Python and experience with relevant libraries (PyTorch, scikit-learn)
Knowledge of deep learning frameworks and architectures
Experience with statistical analysis and experimental design
Familiarity with version control (Git) and reproducible research practices

Preferred qualifications/bonus:

Familiarity with NGS assays such as single-cell and spatial transcriptomics
Familiarity with concepts of domain adaptation or Out of Domain Generalization (OOD) in Machine Learning
Experience with bioinformatics workflows and pipelines

Please submit your CV in English

What we offer

Flexible work organization
Friendly and informal working environment
Opportunity to work with an international team with high technical and scientific backgrounds

Recruitment Process & Security

Please complete the form and submit your CV.
Owkin is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, sex, gender, sexual orientation, age, color, religion, national origin, protected veteran status or on the basis of disability.
Owkin is a great place to work. Unfortunately, being a coveted workplace means we are vulnerable to recruitment phishing scams. We urge all job seekers and candidates to be wary of potential scams. Most of these have individuals posing as representatives of prominent companies, including Owkin, with the aim of obtaining personal, sensitive, or financial information from applicants. These scams prey upon an individual’s desire to obtain a job and can sometimes “feel” like a genuine recruitment process. Some red flags are identified below. Should you encounter a recruitment process that claims to be for Owkin but is not consistent with the below, please do not provide any personal or financial information:
Legitimate Owkin recruitment processes include communication with candidates through recognized professional networks, such as LinkedIn.
Communication is always through an official Owkin email address (from the @owkin.com domain), over the phone or though our applicant tracking system (Greenhouse).
The Owkin talent team do use platforms such as LinkedIn and Job Teaser, however if you have any concern or doubt about this contact, please ask for them to send an email from @Owkin.com.
The Owkin talent team will not solicit personal data from candidates during the application phase including, but not limited to, date of birth, social security numbers, or bank account information;
Legitimate Owkin interviews may be conducted over the phone, in person, or via an approved enterprise videoconferencing service (Google Meets). They will not occur via Signal, Telegram or Messenger
Owkin offers of employment are based on merit and only extended once a candidate has interviewed with members of the talent and hiring team. Offers will be extended both verbally and in written format.