31 Jan 2024
Job Information
- Organisation/Company
Aqemia- Research Field
Computer science- Researcher Profile
Recognised Researcher (R2)- Country
France- Application Deadline
29 Feb 2024 - 00:00 (UTC)- Type of Contract
To be defined- Job Status
Full-time- Hours Per Week
To be defined- Is the job funded through the EU Research Framework Programme?
Not funded by an EU programme- Is the Job related to staff position within a Research Infrastructure?
No
Offer Description
About the team you'll join
As a Machine Learning Research Intern, you'll join a team of engineers and researchers
building algorithms to improve and accelerate our internal drug discovery pipeline.
Your role as a data engineer at Aqemia
- You will explore a particular topic in depth, with responsibility for bibliographic review,
- Representation learning on proteins and small molecules.
- Pre-training and/or fine tuning of neural networks applied to proteins and small molecules.
- Molecule generation in a constrained chemical space.
- Generative modeling of protein-ligand complexes.
implementation, and training/evaluation of models on public and proprietary data. The topic of
the internship is open to discussion and can be tailored to your skills and interests. Possible
topics include:
Your internship should last between 4 and 6 months, and can start as early as March 2024.
>
The competencies we are looking for
- You are a Masters student in Computer Science, Applied Mathematics, Bioinformatics, or a related field.
- You are actively interested in the field of machine learning, and enjoy keeping up to date with current developments.
- Your knowledge of mathematics and statistics allows you to understand and critically evaluate research papers from the field.
- You are comfortable with Python as a programming language, and ideally have hands-on experience with the implementation (using PyTorch/Jax/Tensorflow), training, and evaluation of deep learning systems.
- You are curious and eager to spend time learning new topics from people with diverse backgrounds, and believe that machine learning can play a pivotal role in biology and chemistry for drug discovery.
- Nice-to-haves:
- Experience in representation learning, generative modeling, or reinforcement learning.
- You're interested in complex structured data such as graphs, point clouds, and text.
- Knowledge in biology and/or chemistry/chemoinformatics is a strong plus.
About who we are and our workplace environment
• We signed a contract with Sanofi of $140M to accelerate their drug discovery
• Our approach is completely unique in the industry as we use AI & deep physics to discover new drugs
• We are a team of +50 people from world-class institutions (AstraZeneca, GSK, Sanofi, Harvard, Ecole Normale Supérieure, Ecole Polytechnique, BCG)
• Our Founders boast : 10+ years experience in research at Ecole Normale Supérieure in Paris, not to mention a stint in Oxford and Cambridge / 10+ years experience in strategy consulting at BCG.
• We are located in the center of Paris (1 Bd Pasteur), with a possibility of up to 2 days of remote work.
• We are part of the French Tech 2030 program (https://lafrenchtech.com/fr/la-france-aide-les-startup/french-tech-2030/ ).
• Our working language is English
• We work for a mission: joining us means bringing your own impact on changing the way medicines are discovered and be involved in shaping the direction of our fast growing business and team.
If you feel that you fit only 70% to 80% of this job description but you're still excited to join, then please get in touch!
Aqemia is an Equal Employment Opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion or belief, sex, sexual orientation, gender perception or identity, national origin, age, marital status, disability status or any other basis under applicable law.
Requirements
Additional Information
Work Location(s)
- Number of offers available
- 1
- Company/Institute
- Aqemia
- Country
- France
- Geofield
Where to apply
- Website
https://illbeback.ai/job/machine-learning-research-internship-3/?utm_source=eur…
STATUS: EXPIRED
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