Chargé de comptes IARD Grands comptes publicsH / F

Lindt & Sprüngli; Paris; Sur place; EUR 40 000 - 60 000; Plein temps

Résumé du poste

Join a pioneering start-up at the forefront of AI and biology, dedicated to transforming healthcare through Generative AI. As a Research Scientist, you will leverage your expertise in deep learning and interdisciplinary research to develop innovative solutions that redefine the future of medicine. Collaborate with a team of visionary scientists and contribute to groundbreaking advancements in large biological models. If you're passionate about pushing the boundaries of what's possible and making a global impact, this is the perfect opportunity for you to thrive in a dynamic and inclusive environment.

Qualifications

• PhD in AI, ML, or related field with a strong research background.
• Skilled in deep learning frameworks and interdisciplinary research.

Responsabilités

• Develop and implement deep learning models in AI and biology.
• Contribute to top-tier AI/ML and biology journals and conferences.

Connaissances

Deep Learning

Machine Learning

Artificial Intelligence

Statistical Analysis

Optimization

Graph Algorithms

Interdisciplinary Research

Formation

PhD in Computer Science or related field

Post-PhD experience

Outils

JAX

TensorFlow

PyTorch

Description du poste

Research Scientist (AI) - Cell & Tissue Modeling

Headquartered in Silicon Valley, we are a newly established start-up, where a collective of visionary scientists, engineers, and entrepreneurs are dedicated to transforming the landscape of biology and medicine through the power of Generative AI. Our team comprises leading minds and innovators in AI and Biological Science, pushing the boundaries of what is possible. We are dreamers who reimagine a new paradigm for biology and medicine.

We are committed to decoding biology holistically and enabling the next generation of life-transforming solutions. As the first mover in pan-modal Large Biological Models (LBM), we are pioneering a new era of biomedicine, with our LBM training leading to ground-breaking advancements and a transformative approach to healthcare. Our exceptionally strong R&D team and leadership in LLM and generative AI position us at the forefront of this revolutionary field. With headquarters in Silicon Valley, California, and a branch office in Paris, we are poised to make a global impact. Join us as we embark on this journey to redefine the future of biology and medicine through the transformative power of Generative AI.

Key Responsibilities :

1. PhD (or evidence of equivalent level of expertise) in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field
2. Proven track record in research and innovation demonstrated through contributions in top-tier AI / ML (e.g., NeurIPS, ICML, CVPR, ECCV, ICCV, ICLR) and / or core biology (e.g., Nature, Science, or Cell) journals and conferences
3. Skilled in developing, implementing, and debugging deep learning methods / models in popular frameworks, such as JAX, TensorFlow, or PyTorch, with an interest in generative models, graph neural networks, or large-scale deep learning applications
4. A strong theoretical foundation (statistics, optimization, graph algorithms, linear algebra) with experience building models ground up
5. A passion for interdisciplinary research (with an emphasis on the intersection of AI and Biology), and willingness to acquire necessary domain knowledge
6. Motivated and self-driven with the ability to operate with partial and incomplete descriptions of high-level objectives (as is typical in a start-up environment)
7. Evidence of familiarity and utilization of software engineering best practices (version controlling, documentation, etc), and open-source contributions, especially if used by others

Nice to Have :

1. 3+ years of post-PhD experience in an industry or postdoc role
2. Prior experience working at either a start-up or top research industry labs (e.g., OpenAI, FAIR, Deepmind, Google Research)
3. Hands-on prior experience working at the intersection of AI and Biology
4. Experience in large-scale distributed training and inference, ML on accelerators

Preferred Qualifications :

1. Experience with cell-level data, particularly single-cell RNA-sequencing data.
2. Experience with tissue-level data, particularly spatial transcriptomics, spatial proteomics, or microscopy (e.g. H&E, IF, IHC).
3. Experience with methods development for aforementioned data types
4. Experience with multimodal or multiscale models (even in other domains, e.g. remote sensing, medical imaging).
5. Deep knowledge of one or more of the following : variational autoencoders (especially biological variants like scVI), vision transformers, graph neural networks, neural fields, diffusion models, and self-supervised learning.

Join us as we embark on this journey to redefine the future of biology and medicine.

We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.