Please refer to attached PDF for company info & benefits

THE ROLE

Join the HITS AI Research Team to develop the core AI models behind HyperLab — our platform for drug efficacy prediction, pharmacological property prediction, and molecular design. You'll work alongside chemists, biologists, and engineers who share one goal: building AI that drug discovery scientists actually use.

Eligible for Korean Industrial Research Personnel (전문연구요원) status.

WHAT YOU'LL WORK ON

1. Ultra-Large Chemical Space Exploration

Hyper Screening X — our GFlowNet-based model generates drug candidates across tens of trillions of synthetically accessible molecules. Work on multi-objective optimization (activity, ADMET, protein-ligand interaction), scaffold constraints, pocket-conditioned generation, and so on.

2. Chemical Reaction Prediction & Lab Autonomy

Build AI for the Design-Make-Test-Analyze loop: retrosynthesis, reaction condition prediction, yield optimization, and closed-loop integration with robotic synthesis platforms.

3. Virtual Cell

Predict drug–cell responses by integrating molecular and omics data. Build interpretable models that link molecular interactions to cellular phenotypes. Handle batch effects and zero-shot generalization to new drugs and cell lines.

4. AI for New Drug Modalities

Extend predictive and generative models toward peptides, nucleic acids, antibodies, ADCs, and TPD (PROTAC, molecular glues). As a participant in the K-Fold project — Korea's AI-specialized foundation model initiative — we drive the productization of cutting-edge co-folding models.

5. ADMET Prediction

Develop reliable models for pharmacokinetic properties across in vitro, in vivo, and clinical stages. Work on metabolic site prediction, drug-drug interactions, toxicophore detection, and so on.

WHAT WE'RE LOOKING FOR

● Understand the research areas above deeply enough to picture yourself working on them

● Drive your own research cycle: observation → hypothesis → experiment → insight

● Track and quickly internalize state-of-the-art methods from top-tier conferences

● Gather and curate data with a deep understanding of how it is generated

● Collaborate across functions to validate and productize AI models

● Use AI tooling (Claude Code, etc.) to accelerate your own work

● Operate comfortably in Linux server environments (clusters, job schedulers)

NICE TO HAVE

● PhD in deep learning–related fields, or 3+ years of industry / research experience

● Publications at top-tier AI conferences (ICLR, ICML, NeurIPS, AAAI, ECCV, CVPR, ACL, EMNLP, KDD, etc.)

● Strong competition results (Kaggle, Dacon)

● Background in chemistry, biochemistry, or life sciences

● AWS proficiency (Bedrock, SageMaker, EC2, S3, ParallelCluster, EBS / EFS / FSx)

GET IN TOUCH

HITS Recruitment Team | recruit@hits.ai | career.hits.ai | hyperlab.ai