*Postdoctoral Researcher/Research Engineer Position on “Multimodal Graph*
*Generative Models**with applications to bio/medical domain”*
@DaScim, LIX, Ecole Polytechnique, Paris, France
https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.lix.polytechnique.fr%2Fdascim%2F&data=05%7C02%7Cuai%40engr.orst.edu%7C307cbda3b455470bfa1f08dc4f535851%7Cce6d05e13c5e4d6287a84c4a2713c113%7C0%7C0%7C638472466580793459%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=%2BDTe0jgHCpM1PVLFbFWPx0INPn%2BKbZSOIZ5PSXSCCjU%3D&reserved=0
Graph generative models are recently gaining significant interest in
current application domains. They are commonly used to model social
networks, knowledge graphs, and protein-protein interaction networks.
The research to be conducted during this project will capitalize
on current results of the group on generative models for proteins and
graphs[1][2]. We will investigate the challenges of multi modality in
the context of definingarchitectures for graph generation under the
proper prompt. We expect our designed architectures to be useful in
different areas including molecule design, medical data generation, bio
related data .
Candidate Profiles Candidates must have at least two of the following
• a recent PhD degree in either Computer Science, Mathematics,
Chemistry, Biology or
Physics,
• analytical skills and creative thinking with a hard working attitude,
• good programming skills in deep learning (PythonPytorch).
Ideally we are also searching for candidates with the following desired
qualifications
• strong mathematical background (including Probability, Statistics and
Linear Al-
gebra),
• Machine and Deep Learning skills (architecture design and
optimisation, good under-
standing of Transformers or Graph Neural Networks),
• an understanding of biological application domains,
• a sound publication record with visible impact.
*Funding *
The funding for this position is available for 24 months renewable.
Applications Interested candidates should send an email addressed to
Michalis Vazirgiannis (mvaz...@lix.polytechnique.fr) /by April 2,
2024/and attach the following
• a cover letter including a brief presentation of their academic record
and motivation
as well as relevant skills and experience.
• a full CV with detailed grading information for the acquired degrees.
We will interview candidates on a rolling basis and will aim to fill
this position as soon as
possible.
**
*Location*
This position would require you to work from our offices in the
/Computer Science//Laboratory of ´Ecole Polytechnique in the broader
area of Paris/.
´Ecole Polytechnique is the premier engineering University of Franceand
a founding member of the recently established Institut Polytechnique de
Paris (whichentered the international rankings in high positions).
Famous scientists (including Nobelprize recipients) and industrial
leaders are alumni of the school, offering an exceptional environment
for research in the fast growing excellence pole of Saclay, hosting a
rich ecosystemof industrial and academic research centers a few
kilometers south of Paris. Additionally,it offers ample computing and
recreation resources and facilities on the University campus.The Data
Science and Mining group, in which you would be integrated, has already
hadsignificant impact in local and international research and industrial
activities with severalhigh-impact publications and successful
industrial projects.
Timeline.
-Application deadline: April 2, 2024
-Contract start: any time before September 2024
[1] Prot2Text: Multimodal Protein's Function Generation with GNNs and
Transformers
H. Abdine, M. Chatzianastasis, C.Bouyioukos, M. Vazirgiannis, AAAI 2023,
https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Farxiv.org%2Fabs%2F2307.14367&data=05%7C02%7Cuai%40engr.orst.edu%7C307cbda3b455470bfa1f08dc4f535851%7Cce6d05e13c5e4d6287a84c4a2713c113%7C0%7C0%7C638472466580793459%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=lh6rN0NSg757utmy9EUHYARQcfSNXqe6%2FhTvjFgJwHg%3D&reserved=0
[2] Neural Graph Generator: Feature-Conditioned Graph Generation using
Latent Diffusion Models Iakovos Evdaimon, Giannis Nikolentzos, Michail
Chatzianastasis, Hadi Abdine, Michalis Vazirgiannis,
https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Farxiv.org%2Fabs%2F2403.01535&data=05%7C02%7Cuai%40engr.orst.edu%7C307cbda3b455470bfa1f08dc4f535851%7Cce6d05e13c5e4d6287a84c4a2713c113%7C0%7C0%7C638472466580793459%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=sQD7zs8L%2FhDaOw9yj%2BVViAUcEenpKwze6OTZllZnHJE%3D&reserved=0
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