When someone asks, “What are the basic technical questions in interviews?”, they often want a shortcut—maybe a list they can cram. But interviewers aren’t looking for a list-memorizer. They want problem solvers. Thinkers. People who know how and why—not just what. This blog isn’t just about questions—it’s about strategies across disciplines like engineering, science, math, and computer science, to help you build depth, structure your preparation, and walk into any technical interview with clarity and confidence.
Engineering: Think Systems, Not Subjects
Engineering technical questions are designed to reveal your ability to apply fundamental concepts to real-world constraints.
Strategy:
1. Master first principles, not just formulas
- Don’t just memorize Ohm’s Law or Bernoulli’s equation—understand where they come from and when they break down.
- For example, don’t say “F = ma” by default. Ask: What frame am I in? Are we assuming constant mass? Is friction negligible?
2. Think like a designer
- For example, in mechanical or civil engineering, when asked about material selection or load-bearing structures, imagine constraints: weight, cost, durability, manufacturability.
- Electrical engineering questions may ask you to simplify a circuit or explain how a signal behaves. Instead of racing to calculate, pause to outline the behavior first.
3. Communicate process over perfection
- Many candidates lose points not because they’re wrong, but because they’re silent.
- Say things like: “I’d first identify constraints… then I’d choose a model… and verify assumptions…”
Science: Model the World Logically
Science-based interviews (physics, chemistry, biology, life sciences) look for conceptual clarity and your ability to model dynamic systems.
Strategy:
1. Explain the ‘why’ behind observations
- Interviewers want you to connect observations to theories. For example, why does a reaction rate increase with temperature? Not just “collision theory,” but how increased kinetic energy changes molecular behavior.
2. Practice tiered explanations
- Level 1: To a 10-year-old (clear and visual)
- Level 2: To a peer (technical, concise)
- Level 3: To an expert (with jargon and references)
This flexibility shows you really understand what you’re talking about.
3. Use process thinking for biological systems
- If asked about something like “how does insulin work?”, walk them through the sequence of events: trigger → signal transduction → response → feedback.
- Biological systems are interconnected—practice “zooming in” to molecules and “zooming out” to physiology.
Computer Science: Logic Before Language
Whether you’re from CS or not, basic programming/data questions are common. But success doesn’t lie in syntax—it lies in logical thinking.
Strategy:
1. Think in terms of inputs, outputs, and edge cases
- Given a string or a list—what’s the goal? What happens with null input? Large input? Repetitive elements?
2. Break problems into functions, not code
- Before coding a solution, outline it:
“First, I’ll check the base case… then loop through… if I find a match, I’ll return…”
3. Learn to analyze time and space
- Even basic questions like sorting or searching can become excellent if you discuss complexity:
“This works, but it’s O(n²)… I can try a hashmap for O(n).”
Mathematics: Structure and Simplify
Even non-math majors face logical reasoning and quantitative problems. Here’s how to tackle them like a pro.
Strategy:
1. Start with what’s given and what’s asked
- Many errors happen because the problem isn’t read clearly. Write down inputs, variables, units.
2. Look for hidden patterns
- Whether it’s a number puzzle or a geometry problem, ask: Is this symmetric? Is it increasing linearly? Can it be factorized?
3. Explain every step like teaching a peer
- Even if your answer is wrong, you earn points if your method shows thoughtfulness and structure. Practice with puzzles and explain your reasoning aloud.
Interdisciplinary Roles: Synthesis is the Superpower
Today’s interviews often cut across boundaries—e.g., biotech startups want candidates who understand biology and data. Environmental engineers may need chemistry and policy knowledge.
Strategy:
1. Prepare short concept maps
- E.g., If you’re in biotech, be able to sketch how PCR → sequencing → data analysis → diagnostics.
- Understand not just what happens at each stage, but also why it matters.
2. Show curiosity
- If you don’t know something, say, “I haven’t worked with that directly, but I understand the principle. I believe it’s like…”
- Don’t bluff. Interviewers value intellectual honesty and eagerness to learn.
3. Case-based reasoning
- Interdisciplinary interviews often go, “Suppose a company wants to develop a biosensor…”
Your answer must touch on chemistry, materials, electronics, business—all in one.
Think: What is the goal? What are constraints? What tradeoffs can I manage?
Practice Like It’s a Conversation, Not an Exam
Final Strategies:
- Simulate: Don’t just solve alone. Use tools like AIPrepX for voice-based, timed, and layered mock technical interviews.
- Debrief: After each mock session or real interview, review your thought process—not just whether the answer was correct.
- Feedback loop: Practice → Reflection → Refine → Repeat.
In Summary
There’s no shortcut—but there’s a strategy:
| Domain | Key Focus |
| Engineering | Systems, trade-offs, constraints |
| Science | Cause-effect modeling, explanations |
| CS | Logic before code, edge cases |
| Math | Pattern recognition, structured steps |
| Interdisciplinary | Integration of ideas, clarity under complexity |
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