Phd Computer Science Problem-solving Expert

2 weeks ago

Andaman and Nicobar Islands, India Cutting Edge Search Full time

**Budget - USD 15 - 18 Hourly**
**Contract Duration - 6 months**

**Role Overview**:
**Day-to-Day Responsibilities**:
In this role, you will tackle advanced computer science challenges in AI, machine learning, and data analysis, while developing innovative, research-driven solutions. Sample tasks include:

- Algorithm Development: Design and implement optimized algorithms for processing and analyzing large datasets, focusing on performance and scalability.
- AI Model Building: Develop machine learning models for tasks such as image recognition, natural language processing, and predictive analytics, using state-of-the-art research techniques.
- Data Integration & Visualization: Integrate data from structured and unstructured sources, generating clear visualizations and actionable insights.

**Core Skills and Requirements**:

- Computer Science Proficiency: Strong foundational knowledge in algorithms, data structures, machine learning, AI, and data processing.
- Problem-Solving Ability: Creativity and systematic thinking to address complex computational challenges, with a focus on efficiency.
- Technical Expertise: Experience with programming languages (e.g., Python, Java, C++) and data analysis/machine learning libraries (e.g., TensorFlow, PyTorch) along with big data frameworks (e.g., Hadoop, Spark).
- Research Skills: Ability to frame computational challenges as research questions, design experiments, and evaluate findings.
- Communication: Strong written and verbal skills for presenting technical concepts and research outcomes.

**Preferred Qualifications**:

- PhD or Master's degree in Computer Science or a related field, ideally with a focus on AI, machine learning, or data science.
- Proven research experience in AI or related areas, either in academia or industry.
- Experience with AI tools (e.g., TensorFlow, PyTorch) and familiarity with cloud computing platforms.
- Background in handling large-scale datasets, multi-modal data, and complex system architectures.

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